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Industrial and Production Engineering

Industrial and production engineering research papers/topics, manufacturing of wear resistant clads for slurry/tailings pump impellers via laser cladding (lc)..

Abstract: Wear is a huge problem in the mining industry as it depreciates the assets invested. The industry is looking at efficient refurbishment technologies to repair its equipment so as to enhance its service life. This thesis focuses on the development of wear resistant clads via laser cladding (LC) process to mitigate the problem of degradations in slurry tailings’ pump impeller made of 304L stainless steel. A critical literature review indicates that Tribaloy T-800 and Stellite 6 pow...

A review on wingtip devices for reducing induced drag on fixed-wing drones

Abstract: This review paper presents and analyzes previous studies on wingtip devices mainly to reduce induced drag on fixed-wing aircraft and drones. Some of the parameters discussed are the different types of winglets, cant angles, and adjustable wing structures. And these are compared against performance measures including reduced drag, fuel consumption, and improved endurance. This study aims to explore the optimized design of a wing that will give maximum drag reduction for fixed-wing d...

Defect Analysis and Productivity Enhancement of Crankcase Casting through Pareto Analysis, POKAYOKE and QC Tools

Abstract: Productivity is a very important aspect in any organization. Productivity means output obtained with respect to how much input is provided. To increase the productivity of any organization it is necessary to study and analyze the rejection data of that organization. This research focuses on the need of following a proper methodology in solving any particular problem. The defects were prioritized using QC tools, Pareto analysis. This research emphasizes on the importance of focusing ...

DART IMPACT TESTER PRIMA SERIES

Presto is the market leader in Packaging Testing Instruments with over 38 Years’ experience. A National Award Winner for Quality Product from the Government of India. Presto builds low-costtesting instrumentsfor the plastic and packaging industry.  

Ergonomics Study of the Incidence of Musculoskeletal Disorder Among the School Teachers in Egba Division of Ogun State Nigeria

Musculoskeletal pains (MP) especially the lower back, leg, neck and shoulder pain were the common complain among the classroom teachers due to prolong desk working and standing in the classroom. The study was conducted among the primary and secondary school classroom teachers in randomly selected two hundred and seven (207) schools in Egba division of Ogun State, Nigeria.

Anthropometric Determination of Body Height from Foot Length of Adults in Abeokuta Southwest Nigeria

Forensic identification of an individual in this time of unrest in some parts of the world cannot beo .overemphasized. The study was conducted to investigate and determine the body height (Bh)from foot length (Fl). The Bh and Fl of Two hundred and sixty (260) adults(male and female) of participate in Abeokuta Southwest Nigeriaa, ages ranged between 24 years and 55 years

Development of A Generalised Solution for The Performance Measures of Queuing Systems

ABSTRACT This study developed computer software with the capacity to provide a generalized solution to queuing problems involving laborious, time consuming and complex mathematical approach of evaluating the performance measures of queuing systems when it was applied in the analysis of the six (6) fundamental performance measures of thirty (30) different organizations representing the six (6) queuing systems; the result was compared with that of mathematical computations and 97.22% complianc...

Preprocessing and Simulation of Out of Hospital Cardiac Arrest Outcomes Data

Out-of-hospital cardiac arrest (OHCA) is a cessation of cardiac mechanical activity that occurs outside of the hospital setting and is confirmed by the absence of signs of circulation. OHCA affects nearly 1000 adult Americans every day, with overall survival rate of 10.4%. Based on previous work in this subject I try to calculate the joint probability distributions of the neurological outcomes of the OHCA outcomes in our records, based on the Event Demographics, Field Care, and Hospital Care....

Optimization Of Transportation Costs In Supply Chain Management (A Case Study Of Coca-Cola Plants In Nigeria)

ABSTRACT In the manufacturing sector management of the supply chain expenses has been identified as major costs driven problem. For many years, researchers and practitioners have concentrated on the individual processes and entities within the Supply Chain. Recently, however, many companies have realized that important cost savings can be achieved through the reduction of transportation costs throughout their Supply Chain. As companies began realizing the benefits of optimizing transportatio...

The Combined Application of Quality Function Deployment and Pareto Analysis for Hotel Services Improvement

Introduction For several years, Quality Function Deployment (QFD) has been at the leading edge of research and development in many fields (Barnett and Raja, 1995; Chiou and Tong, 2001; Han et al., 2001; Pitman et al., 1996; Pramod et al., 2007; Walker, 2002; Wang, 2007). QFD evolved as a way to incorporate knowledge about the needs and desires of end-user customers into all stages of the design, manufacture, delivery and support of products and services (Einspruch, 1996; Griffin and. Hauser, ...

A Framework For an In-House Development of Educational Management Information System

ABSTRACT A large percentage of Nigerian educational institutions use manual and paper- based system for collecting, processing, and disseminating information. This approach results in inefficient utilization of resources, low productivity and stunted growth of the educational sector. In this study the in-house users- development approach has been used to develop a computer based Educational lnformation Management System (8MS) for a typical University academic department. The existing work Sy...

A Genetic Algorithm for Job Scheduling in Two Machine Flow Shop Problem

Abstract This paper considers the problem of scheduling in flow-shop by Johnson's Algorithm method, Branch and- Bound Algorithm method and Genetic Algorithm-seethed to find an optimal sequence for n jobs m-machine problem based on minimum elapsed time.ln scheduling the two machine flow shop problem F211 I C, one has to determine a schedule that minimizes the sum of , finishing times of an arbitrary number of jobs that need to be executed on two machines, such that each job must complete proce...

Optimum Allocation of Silicone Oil in Flexible Polyurethane Foam Production

ABSTRACT The high cost of purchasing good quality flexible polyurethane foam called for this project work, which examines the possible reduction in the cost of production which will eventually lead to reduction in all overall market cost. Process optimization technique was adopted using gradual chemical variance method for the foam surfactant (silicone oil) to locate the optimum silicone oil quantity required as against the usual practice of ipart of silicone oil to 100 part of polyol for 20...

Genetic Algorithm Approach For Optimisation Of Silica Extraction For Micro-Crystalline Silicon Production

Solar collectors mainly produced from poly-crystalline (P-Si) and micro-crystalline silicon (µ-Si) are in high demand in Nigeria due to persistent power challenges. The silicon are mostly imported and µ-Si is preferable due to its low cost. The µ-Si is extracted from Rice Husk (RH). However, the procedure of setting its optimal process variables (temperature, time and solvent volume) which are determinants of the reduction in cost is under reported in the literature. The aim of this study ...

Improvement Of Facility Layout Using Systematic Layout Planning: A Case Study Of Numerical Machining Complex Limited

ABSTRACT The facilities layout problem is an integral part of facilities planning that aims to systematically arrange and locate all production units within a facility with an objective of improving the production operations of a company. Numerical Machining Complex is planning to improve the production of its manufacturing operations in its machining and fabrication workshop. It seeks to enhance the performance of the existing workshop in terms of efficiency, productivity, and space utiliza...

Industrial and Production Engineering is an interdisciplinary engineering discipline that includes manufacturing technology, engineering sciences, management science, and optimization of complex processes, systems, or organizations. Afribary curates list of academic papers and project topics in Industrial and Production Engineering. You can browse Industrial and Production Engineering Project topics, Industrial and Production Engineering thesis topics, Industrial and Production Engineering seminar topics, research papers, termpapers topics in Industrial and Production Engineering. Industrial and Production Engineering projects, thesis, seminars and termpapers topic and materials

Popular Papers/Topics

Evaluation of the effectiveness of quality control in dangote cement plc, critical analysis of the recent poor performance of engineering students in engineering mathematics: a case of nnamdi azikiwe university,, evaluation and assessment of relocation from a city to the outskirts: case study dhl gävle sweden, assessing and monitoring open pit mine, the role of informal sector in employment generation in ilorin, kwara state nigeria, development of a maintenance strategy for flour milling industry: a case study of corn milling industry in kenya, development of low cost point of care device for detection of schistosoma haematobium, application of fuzzy clustering data mining approach to garment sizing problem, electrodialysis, productivity improvement in manufacturing industries, an algorithm for job scheduling in 2-machine flow shop problem, a bicriteria model for production planning in a toothpaste factory.

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The Department of Industrial Engineering has seven research areas for students to choose from. Every research area is unique and has its own research theme and course work.

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Research in applied statistics and statistical learning investigates technologies and methodologies in the area of data science. It helps drive business value, improve decision-making, understand human relationships and transform data into knowledge.

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Research in financial engineering integrates methods and knowledge from mathematics, statistics, economics, operations research, and computer science.

Research in healthcare engineering integrates and develops operations research, management science, analytics, and computer science methodologies with applications to, and motivation from, problems in developing cost effective health and humanitarian systems.

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Research on computational social science focuses on the social and technical dynamics within formal and informal organizations.

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Research in Logistics and Operations focuses on supply chain management, product development, and service operations.

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Industrial Engineering & Operations Research

Department of industrial engineering & operations research.

How many fast passes should an amusement park distribute? How can a newspaper vendor balance fixed costs against uncertain demand? Why do you wait “forever” for a bus, only to see two or three arrive at the same time? If you’ve ever thought about these kinds of problems, you’ll like it here. Industrial Engineering & Operations Research combines two disciplines focused on the operation of complex systems. Students learn statistically rooted frameworks to model and solve systems-level engineering problems. Industrial Engineering is about making people and processes safer, more efficient and more effective. Operational researchers use their analytical and creative skills to develop better systems and operational procedures. There’s work in this field across a wide range of industries, including manufacturing, communications, transportation, entertainment, finance, military, healthcare and pharmaceuticals.

Why choose Berkeley?

Because our department is considered one of the finest schools of industrial engineering and operations research in the world. Because our department is ranked second in the U.S. by the National Research Council and has received millions of dollars of industry and government funding to support research projects. Because our faculty author the textbooks used to teach these subjects at institutions worldwide. The many awards they’ve won include the Franz Edelman Award for Management Science Achievement, the Nicholson Award, the ACM Turing Award, the Lanchester Prize and the Fulkerson Prize.

Our faculty members are globally renowned in their application areas, from semiconductor manufacturing and the design and deregulation of energy markets to supply-chain management, robotics and discrete event simulation. And they’ve made major advancements in the theory of operations research, including algorithm design, integer programming, non-linear programming and stochastic modeling.

Need more details? Learn about the Department of Industrial Engineering & Operations Research and its programs .

Research Methodology in Management and Industrial Engineering

• © 2020
• Carolina Machado 0 ,
• J. Paulo Davim   ORCID: https://orcid.org/0000-0002-5659-3111 1

Department of Management, School of Economics and Management, University of Minho, Campus Gualtar, Braga, Portugal

You can also search for this editor in PubMed   Google Scholar

Department of Mechanical Engineering, University of Aveiro, Campus Santiago, Aveiro, Portugal

• Discusses principles, strategies, models, techniques, applications and methodological options to develop research in management and industrial engineering
• Helps the reader to answer the questions that arise when developing the research
• Unique book on research methodology focusing on the specific discipline of management and industrial engineering

Part of the book series: Management and Industrial Engineering (MINEN)

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Table of contents (6 chapters)

Front matter, a reviewer’s perspective: which mistakes do authors often make in qualitative international business research.

• Tiia Vissak

Evaluating Corporate Social Responsibility/Sustainability Strategic Maturity: Some Methodological Options

• António Marques-Mendes, Maria João Nicolau dos Santos

Technology Forecasting: Recent Trends and New Methods

• Gema Calleja-Sanz, Jordi Olivella-Nadal, Francesc Solé-Parellada

Methodology Used for Determination of Critical Success Factors in Adopting the New General Data Protection Regulation in Higher Education Institutions

• José Fernandes, Carolina Feliciana Machado, Luís Amaral

Emotional Intelligence and Leadership: A 360-Degree View in the Electronics Industry in Portugal

• José Rebelo dos Santos, Lurdes Pedro, Sandra Nunes

The Role of Institutional Leadership in Employee Motivation, Satisfaction, and Personal Development— Design of a Research Proposal

• Maria Heliodora Matos, Carolina Feliciana Machado

Back Matter

• decision analysis
• methodological issues
• research project design
• phenomenological research
• positivistic research
• data collections
• sampling techniques
• Engineering Economics

About this book

The main aim of this book is to provide a channel of communication to disseminate knowledge between academics and researchers, with a special focus on the management and industrial engineering fields. This book can serve as a useful reference for academics, researchers, managers, engineers, and other professionals in related matters with research methodologies. Contributors have identified the theoretical and practical implications of their methodological options to the development and improvement of their different study and research areas.

Editors and Affiliations

Carolina Machado

J. Paulo Davim

About the editors

J. Paulo Davim received his Ph.D. degree in Mechanical Engineering in 1997, M.Sc. degree in Mechanical Engineering (materials and manufacturing processes) in 1991, Mechanical Engineering degree (5 years) in 1986, from the University of Porto (FEUP), the Aggregate title (Full Habilitation) from the University of Coimbra in 2005 and the D.Sc. from London Metropolitan University in 2013. He is Senior Chartered Engineer by the Portuguese Institution of Engineers with an MBA and Specialist title in Engineering and Industrial Management. He is also Eur Ing by FEANI-Brussels and Fellow (FIET) by IET-London. Currently, he is Professor at the Department of Mechanical Engineering of the University of Aveiro, Portugal. He has more than 30 years of teaching and research experience in Manufacturing, Materials, Mechanical and Industrial Engineering, with special emphasis in Machining & Tribology. He has also interest in Management, Engineering Education and Higher Education for Sustainability. He has guided large numbers of postdoc, Ph.D. and master’s students as well as has coordinated and participated in several financed research projects. He has received several scientific awards. He has worked as evaluator of projects for ERC-European Research Council and other international research agencies as well as examiner of Ph.D. thesis for many universities in different countries. He is the Editor in Chief of several international journals, Guest Editor of journals, books Editor, book Series Editor and Scientific Advisory for many international journals and conferences. Presently, he is an Editorial Board member of 30 international journals and acts as reviewer for more than 100 prestigious Web of Science journals. In addition, he has also published as editor (and co-editor) more than 125 books and as author (and co-author) more than 10 books, 80 book chapters and 400 articles in journals and conferences (more than 250 articles in journals indexed in Web of Science core collection/h-index 53+/9000+ citations, SCOPUS/h-index 57+/11000+ citations, Google Scholar/h-index 75+/18000+).

Bibliographic Information

Book Title : Research Methodology in Management and Industrial Engineering

Editors : Carolina Machado, J. Paulo Davim

Series Title : Management and Industrial Engineering

DOI : https://doi.org/10.1007/978-3-030-40896-1

Publisher : Springer Cham

eBook Packages : Engineering , Engineering (R0)

Copyright Information : Springer Nature Switzerland AG 2020

Hardcover ISBN : 978-3-030-40895-4 Published: 14 March 2020

Softcover ISBN : 978-3-030-40898-5 Published: 14 March 2021

eBook ISBN : 978-3-030-40896-1 Published: 13 March 2020

Series ISSN : 2365-0532

Series E-ISSN : 2365-0540

Edition Number : 1

Number of Pages : XI, 154

Number of Illustrations : 8 b/w illustrations, 3 illustrations in colour

Topics : Engineering Economics, Organization, Logistics, Marketing , Innovation/Technology Management , Research Methodology

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Berkeley Berkeley Academic Guide: Academic Guide 2023-24

Industrial engineering and operations research.

About the Program

The Department of Industrial Engineering and Operations Research (IEOR) offers four graduate programs: a Master of Engineering (MEng), a Master of Science (MS), a Master of Analytics (MAnalytics), and a PhD. These programs have been developed to meet the needs of individuals with backgrounds in engineering or the mathematical sciences who wish to enhance their knowledge of the theory, development, and use of quantitative models for design, analysis, risk management, and decision-making. This knowledge applies to complex systems in the industrial, service, or public sectors, including energy systems, supply chains, healthcare systems, and financial systems. Students may concentrate on theoretical studies in preparation for doctoral-level research, or on applications of state-of-the-art techniques to real world problems.

Master of Engineering (MEng)

The MEng is a professional, full-time, accelerated professional master's degree program and  is currently a lock-step, two-semester degree program.  Students learn advanced techniques in IEOR and skills that prepare them to lead teams in developing new engineering solutions: skills in managing complex projects, motivating people, and directing financial and operational matters.

Master of Science (MS)

The MS is a full-time technical master's degree program. Students focus on both the theory of IEOR techniques and the application of those techniques. The MS is a terminal degree, meaning that students enrolled in the MS program do not typically continue further into the IEOR PhD program.  

Master of Analytics (MAnalytics)

The 11-month in-person Master of Analytics program trains students in data-driven analytical methods and tools for optimization, statistics, simulation, and risk management with relevant industry context so that the graduates are not only highly skilled in the latest tools and fluent with working with large data sets, but also are able to raise the right questions to develop innovative models and find creative solutions to rapidly changing business and industry challenges, and communicate and implement their solutions.

Doctor of Philosophy (PhD)

The paramount requirement of a doctoral degree is the successful completion of a thesis on a subject within Industrial Engineering and Operations Research. Research areas may include but are not limited to the investigation of the mathematical foundations of and computational methods for optimization or stochastic models, including risk analysis. Research also may be undertaken to develop methodologies for the design, planning, and/or control of systems in a variety of application domains, including supply chains, energy systems, healthcare systems, and financial systems.

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Admission to the University

Applying for graduate admission.

Thank you for considering UC Berkeley for graduate study! UC Berkeley offers more than 120 graduate programs representing the breadth and depth of interdisciplinary scholarship. A complete list of graduate academic departments, degrees offered, and application deadlines can be found on the Graduate Division website .

Prospective students must submit an online application to be considered for admission, in addition to any supplemental materials specific to the program for which they are applying. The online application can be found on the Graduate Division website .

Admission Requirements

The minimum graduate admission requirements are:

A bachelor’s degree or recognized equivalent from an accredited institution;

A satisfactory scholastic average, usually a minimum grade-point average (GPA) of 3.0 (B) on a 4.0 scale; and

Enough undergraduate training to do graduate work in your chosen field.

For a list of requirements to complete your graduate application, please see the Graduate Division’s Admissions Requirements page . It is also important to check with the program or department of interest, as they may have additional requirements specific to their program of study and degree. Department contact information can be found here .

Where to apply?

Visit the Berkeley Graduate Division application page .

Doctoral Degree Requirements

Normative time requirements, normative time to advancement.

Total normative time to advancement is 2-3 years.

Step I:  This process normally takes 1 year (to take the entrance exam).

Step II:  After passing the preliminary or entrance exam, students prepare for their PhD oral qualifying examination. This step lasts one to one and a half years . With the successful passing of the orals, students are advanced to candidacy for the PhD degree.

Normative Time in Candidacy

Step III:  Students undertake research for the PhD dissertation under a three-person committee in charge of their research and dissertation. The students then write a dissertation based on the results of this research. On completion of the research, workshops, and approval of the dissertation by the committee, the students are awarded the doctorate.

Total Normative Time

Total normative time is 4-5 years or 8-11 semesters .

Before Advancement to Candidacy

Doctoral entrance exam.

Every doctoral student is required to take the doctoral entrance examination. Students entering without an MS degree are required to complete all MS degree requirements and may do so by completing the MS course requirements and passing the doctoral entrance exam.  Doctoral students who do not pass the entrance exam are subject to dismissal from the IEOR PhD program.

The entrance examination consists of three parts:

• An optimization exam: Students are required to take  IND ENG 262A  and at least one other course in Group A (see below) to be prepared for this exam.
• A stochastic processes exam: Students are required to take  IND ENG 263A  and at least one other course in Group B (see below) to be prepared for this exam.
• An exam on modeling and applied operations research: Students are required to take two courses in Group C (see below) to be prepared for this exam.

All required courses for the doctoral entrance examination must be taken for a letter grade.

The entrance examination will be offered near the end of every spring semester, approximately one week before finals. Passing the entrance examination is based on both superior performances on all parts of the exam, and on previous coursework. Students are required to take the entire exam at the same time.

In order to take the exam, students are expected to perform sufficiently well in their first-year courses. During the middle of the spring semester, a faculty committee will review the performance of first-year doctoral students, and students who have performed sufficiently well on their coursework and maintained a 3.5 GPA, the College of Engineering's expectation of distinguished scholarship, will be permitted to take the exam.

Students who enter in the fall are expected to take the exam at the end of the spring semester in the same academic year.

The entrance examination will consist of two written exams, in optimization and in stochastics, taken on separate days, and three oral examinations in the areas of optimization, stochastics, and modeling. Each student will be examined by two faculty members in each of the three areas. In optimization and stochastics, each student will be examined on topics related to the two courses taken in the area (in case the student took three or more courses in optimization or stochastics, they should state a preference as to which course will be considered the second). For modeling, the students will be provided with a case study approximately two weeks prior to the exam. Each student is expected to address the case study using applied operations research techniques and present their analysis at the modeling oral exam.

Advanced undergraduate courses in linear algebra (equivalent to  MATH 110 ) are prerequisites for the PhD program. Students who have not taken these courses prior to entering the graduate program are required to do so during their first year.

Some students have specific research interests and goals when they enter a doctoral program; for others, these interests develop in the process of taking courses and preparing for the entrance examination. In either case, it is imperative that students begin their research as soon as possible after completing their entrance examination. One of the important initial steps in this process is finding a faculty member who will agree to supervise the dissertation (thesis advisor). Every student is required to complete at least one unit of independent study with a faculty member each semester after passing the entrance examination until finding a thesis adviser.

A minimum of nine graduate courses is required in the major, including those taken prior to the entrance examination. Usually, these are courses taken in the IEOR department, but to a very limited extent, courses taken in other departments may be counted as part of this requirement. These courses should provide depth in the student's probable research area.

In addition, course work is required in two minor areas. This is a College of Engineering requirement, which specifies that two or three courses (of advanced undergraduate or graduate level) typically represent a minimum program for a minor. This loose wording reflects the diverse needs of the College. In this department, each minor must consist of six units at the graduate level, at least three of which must be taken for a letter grade. A minor may serve either to strengthen theoretical foundations (e.g., measure-theoretic probability theory), or as an area of application (e.g., transportation). At most one course of one minor can be a course from within this department, as long as this course is distinct from the nine courses in the major. Both minors should be selected to strengthen the student's background in his or her research area, and minors are subject to the approval of the head graduate adviser. 

The thesis advisor, once known, should be consulted about all matters regarding the program of study.

Coursework is comprised of an approved study list based on the student’s research interest, which must include the following:

In addition to the courses listed here, many occasionally-offered 290 series courses fit into this category; check with the head graduate advisor about specific courses which may be approved.

Effective Fall 2022, the department requires one of the Group C courses be one of INDENG 250, 251, 253, 254, or 255.

Foreign Language(s)

In addition to English, the program does not require another language.

Qualifying Examination (QE)

The Qualifying Examination is an oral examination with a written component administered by four faculty members. Three of these faculty members are required to be IEOR faculty members and the fourth faculty member must be a Faculty Senate Member from another department with expertise in one of the student’s minor areas of study. Students are expected to take the Qualifying Examination within three semesters after passing the Doctoral Entrance Exam. Priority in department funding (especially NRTs) will be given to students who have passed their Doctoral Entrance Exams and are in their 3rd, 4th, and 5th semesters. Although it is necessary for a student to identify a potential research area and some potential dissertation topics in order to complete this exam, it is not necessary for the student to do a substantial amount of research in the area of the examination.

The student is required to have completed or be currently enrolled in courses that will complete at least one of the two minors at the time of the Qualifying Examination. At least one of the minors completed or being completed at the time of the Examination must consist entirely of courses from outside the department. In addition, at the time of the Qualifying Examination, the student is required to have a specific plan for completing the other minor within two semesters.

Prior to the exam, the student is required to identify a research area (broadly defined) in which he or she will be able to demonstrate expertise during the oral part of the examination. In addition, the student must be prepared to demonstrate expertise in one minor field. The objective of the exam is to assess the student’s ability to demonstrate knowledge in a broad research area, and to identify potential research topics within this area.

At least six weeks prior to the approximate date of the Qualifying Examination, the student must meet with the Head Graduate Advisor and provide the following: a list of topics which will form the basis of the exam (also known as a “syllabus”), a Program of Study that includes all major and minor courses taken or planned (whether or not they are included in the syllabus), a list of faculty members who have agreed to serve on the exam committee, a preliminary draft of the Qualifying Exam Report for the exam committee (also known as a “prospectus” or “technical report”), and approval from the student's advisor of the intended date and topics. The syllabus should include topics from major subject areas, equivalent to several courses, together with topics from one of the minor areas. The Program of Study must be approved by the Head Graduate Advisor before submitting the "Application for Qualifying Examination" via CalCentral to the Graduate Division.

Next the student needs to begin arranging the Qualifying Examination logistics with their Qualifying Exam Committee by determining a date and time when all committee members can attend. The student must also request a room in which the exam can be held. This exam is to be scheduled for three hours, at a time when all Committee members can attend.

At least four weeks prior to the exam and upon approval from the Head Graduate Advisor, the student must submit the "Application for Qualifying Examination" to the Graduate Division. To do so, the student must log in to CalCentral > Student Resources > Higher Degree Committees Form > select Qualifying Exam from the dropdown and enter all information. Students must remember to upload the syllabus and Qualifying Exam Report.  

At least two weeks prior to the exam, the student must submit his or her Qualifying Exam Report to the qualifying exam committee. This report should be in the form of a research proposal, and should include both a substantial survey and critical evaluation of the literature in the likely area of the dissertation, and a potential research agenda in this area. If the student has completed preliminary research in this area, it is also appropriate to include a report of this research in this document. 

The Qualifying Exam document will be reviewed by the three professors who represent the major on the student’s Qualifying Examination Committee, to determine adequacy of preparation for the research area. For students who follow these guidelines and the recommendations of the Graduate Adviser and Thesis Adviser, this usually results in quick approval. However, if preparation is judged to be inadequate, they may recommend additional course work and postponement of this Examination.

The oral portion of the Qualifying Examination has two parts. In the first part, the student presents a 45-minute talk based on his or her Qualifying Examination Report. The Committee will ask questions pertaining to the report and presentation at this time. During the second part of the oral examination, the committee will ask more general questions to determine the student’s level of expertise in the broadly defined research area specified by the student (and described in the syllabus). During this time, the outside committee member will also ask questions about one of the student’s minor areas.

If the student's performance is judged to be unsatisfactory, the Committee may recommend reexamination, possibly after additional preparation has been completed. If the reasons for the unsatisfactory performance are judged to be major and fundamental, the Committee may recommend that a second attempt be denied.

Effective Fall 2022, students who do not pass the Qualifying Examination by their third semester after passing the Doctoral Entrance Examination are subject to progress probation through the Graduate Division and are responsible for payment of their own non-resident tuition.

Time in Candidacy

Advancement.

After passing the qualifying examination, the student should file an application for advancement to candidacy in CalCentral, which sets up a three-person guidance committee for the dissertation. Once this is approved, the student is eligible for reduced fees. After advancing to candidacy, the student is expected to spend full time doing research on his or her dissertation and on related teaching tasks.

Required Professional Development

Teaching opportunities.

The Department of IEOR strives to provide every student with an opportunity to gain teaching experience. Students work as teaching assistants (Graduate Student Instructors, or GSIs), responsible for discussion or laboratory sections, and serve as readers assisting with grading but not conducting independent teaching.

At least once a year after passing the qualifying examination, the student is required to hold a dissertation workshop. Each dissertation workshop has two primary objectives:

• It provides the department an opportunity to review the progress of students who have passed the qualifying examination, toward completion of their doctoral dissertation.
• It facilitates interaction between the student and the dissertation committee and provides the basis for useful and consistent guidance. While the dissertation committee is primarily responsible for providing guidance, feedback from other faculty and from students is sought as well.

During the workshop, the candidate is expected to present a prospective of, and results from, the dissertation research. Dissertation advisers should advise students about the appropriate time for the workshops. However, initiation of the workshops is the student's responsibility. The student needs to notify the department at least one month in advance of the desired workshop date, and coordinate this date with the dissertation committee. At least two weeks prior to each Workshop, the student shall distribute to the Dissertation Committee a report called the “Dissertation Prospectus.” All Workshops, including the Final Workshop, will be open to, and announced to, the IEOR faculty and PhD and MS students.

Each workshop is divided into two parts. The first part is devoted to a public presentation by the student and subsequent discussion. This part is conducted as a seminar and is open to all faculty and students. Graduate students and faculty who have research interests that relate to the workshop are encouraged to attend; this may be their best opportunity to provide constructive feedback to the candidate. (Graduate students who have not yet reached this stage in their own program often find that participating in workshops is a valuable educational experience.) The dissertation committee moderates the presentation and discussion, controls the asking of questions by the audience, and calls an end to the first part of the workshop.

In the second part of the workshop, which immediately follows the public presentation, the dissertation committee and other interested faculty members will reconvene in private with the candidate for the purpose of giving more feedback and specific guidelines for continuing research. At this time, the committee may decide that the candidate's progress is unsatisfactory. Should the committee reach this conclusion, it will be reported in writing, with proper justification, to the candidate and the department chair. The committee may require an additional workshop sooner than one year after the unsatisfactory one. Recurrent failure to present a satisfactory prospectus workshop may result in the disqualification of the student and termination of doctoral candidacy.

Final Workshop

Once the candidate has completed his or her research and completely written the thesis, a final workshop must be scheduled and held. A completed copy of the thesis must be distributed to the committee at least two weeks before this final workshop. This workshop will follow the same format as other workshops. The committee will inform the candidate about any remaining problems or issues with the thesis. If the committee has serious issues with the thesis, it may require an additional final workshop. 

Master's Degree Requirements (MS)

Unit requirements.

Students are required to complete 24 semester units of upper division and graduate coursework, 12 units of which must be graduate courses in the major taken for a letter grade. IND ENG 298 units do not count towards this 12-unit requirement.

All students are required to take 1 unit of IND ENG 298 ; at least one course each from the following categories: Optimization, Stochastic Models, and Modeling (see below); and additional courses.

Beyond these requirements, the program is quite flexible. No more than two units of  IND ENG 299  may be counted toward the degree. The remainder of the program can include electives outside the department. 

All students must take at least one course from each of the following three categories (optimization, stochastics, modeling), as listed below.

Master of Science Thesis (Plan 1)

Students may complete the requirements by writing a thesis, rather than taking a comprehensive examination. The course requirements under the thesis option are the same as under the comprehensive option. A committee of three professors, including one from outside the IEOR Department, will be formed to guide and approve the thesis.

The Comprehensive Exam or Project (Plan 2)

In addition to course requirements, students are required to complete one of two options: a comprehensive exam or a master's project and oral presentation of this project. The structure of the comprehensive exam may vary from year to year but is designed so that students whose curriculum includes 12 units of graduate courses in the major and satisfies the group distribution listed above should be prepared to take the exam. At the current time, the comprehensive exam consists of a short oral presentation to a panel of two or three faculty of a solution to a case study, for which the students will be given at least two weeks to prepare, followed by relevant questions from the faculty panel.

Relation to Doctoral Requirements

In general, the first year doctoral requirements meet the requirements of the MS degree, but the reverse is not necessarily true. Students who are interested in earning a PhD should apply to enter the PhD even if they do not yet have an MS degree. More detailed information on the entrance exam may be found on the Doctoral Degree Requirements tab.

Master's Degree Requirements (MEng)

Minimum number of units to complete degree: 25 semester units.

Technical Course work (must be taken for a letter grade):

• Core Courses:  All students are required to take IND ENG 240 and IND ENG 241 . 
• FinTech students must select two of the following: IND ENG 221 , IND ENG 222 , IND ENG 223  , and  IND ENG 224 . Additionally, FinTech students must take IND ENG 290: Applications of Machine Learning to Electronic Markets. 
• IP & Entrepreneurship Strategy students must take  IND ENG 242A , one additional INDENG 200+ course from an approved list, and   two business courses,  ENGIN 273  and  ENGIN 274 .

Leadership Courses (must be taken for a letter grade):

• All students must complete 8 semester units of core leadership courses from an approved list.  

Capstone Project Courses (must be taken for a letter grade):

• Students must take the capstone integration course each semester.
• All students must complete 5 units of capstone courses: 2 units in the fall semester and 3 units in the spring semester.

Required Technical Courses 

Required leadership courses, required capstone courses, comprehensive technical exam.

Passing the departmental Comprehensive Technical Examination is a required milestone for all IEOR MEng students. The three-hour written exam is administered every year during RRR week of the Fall semester (the last instruction week of the semester). The exam is composed of two parts as follows:

Optimization (90 minutes): Based on INDENG 240 material, the exam questions focus on formulation (modeling) of optimization problems, covering linear, integer, and nonlinear programming problems.

Stochastic Modeling (90 minutes): Based on INDENG 241 material, the exam questions focus on basics of probability theory and stochastic processes, including random variables, conditional expectation, variance and covariance, and Poisson processes.

Comprehensive Leadership Exam

The Fung Institute will administer the MEng Comprehensive Leadership Exam, which will be held early in the spring semester. The format will be an individual, oral exam related to the student’s capstone leadership experience (e.g., teaming, stakeholder management, conflict resolution, and project scoping). The exam details and pass/fail assessment criteria will be shared on bCourses. Please contact Fung Institute staff for more details.

Capstone Project

Students are required to complete a capstone project. The project enables the student to integrate the core leadership curriculum with the concentration and gain hands-on industry experience.

Minimum number of units to complete degree: 29-semester units.

Python Boot camp

All students are encouraged to take a Python boot camp (50 hrs) in preparation for the technical coursework. The Python boot camp is a 0-unit course offered in July or August leading up to the program's start. 

Technical Course work (must be taken for a letter grade)

Elective specialty courses (must be taken for a letter grade).

Students must complete a minimum of 9 units of IND ENG 200-level technical electives for letter grades from an approved list.

SUMMER INTERNSHIP

All students must complete four units of the summer internship (individual study) course (200 hours, typically 20 hr/week over 10 weeks in  May-August) during the final summer semester.

Comprehensive Exam

Passing the departmental Comprehensive Examination is a required milestone for all IEOR MAnalytics students. The three-hour written exam is administered annually during the RRR week of the Fall semester (the last instruction week of the semester). The exam is composed of two parts as follows:

Optimization (90 minutes): Based on INDENG 240 material, the exam questions focus on the formulation (modeling) of optimization problems covering linear, integer, and nonlinear programming problems.

Stochastic Modeling (90 minutes): Based on INDENG 241 material, the exam questions focus on the basics of probability theory and stochastic processes, including random variables, conditional expectation, variance and covariance, and Poisson processes.

IND ENG 210 Python for Analytics 3 Units

Terms offered: Prior to 2007 This introductory course provides students with sufficient background in Python programming language for use in analytics applications as well as potentially conducting research in the area. The course is designed to prepare students for the applied analytics problems and projects they will encounter in advanced analytics courses. It will start with basic programming topics using Python and cover using powerful Python packages such as Numpy, Scipy, Pandas, and Matplotlib that are essential for descriptive, predictive, and prescriptive analytics. Students will work on group projects along with the instructor in order to solidify the lectures into practical experience using Python for analytics. Python for Analytics: Read More [+]

Objectives & Outcomes

Student Learning Outcomes: LEARNING GOALS Upon completion of the course students will have learned how to: ● use Python and core scienti ic packages to solve complex analytics problems; ● develop custom Python scripts and functions to perform analytic computations; ● visualize analytic results in graphical form; ● understand the array of mathematical toolkits provided by the Python packages covered.

Hours & Format

Summer: 2 weeks - 15 hours of lecture and 10 hours of laboratory per week

Additional Format: Fifteen hours of lecture and ten hours of laboratory per week for two weeks.

Additional Details

Subject/Course Level: Industrial Engin and Oper Research/Graduate

Grading: Letter grade.

Instructors: Aswani, Grigas, Pirutinsky

Python for Analytics: Read Less [-]

IND ENG 215 Analysis and Design of Databases 3 Units

Terms offered: Fall 2024, Spring 2024, Fall 2023 Advanced topics in information management, focusing on design of relational databases, querying, and normalization. New issues raised by the World Wide Web. Research projects on current topics in information technology. Analysis and Design of Databases: Read More [+]

Rules & Requirements

Prerequisites: Graduate standing

Fall and/or spring: 15 weeks - 2 hours of lecture and 1 hour of laboratory per week

Additional Format: Two hours of lecture and one hour of laboratory/project per week.

Instructor: Goldberg

Analysis and Design of Databases: Read Less [-]

IND ENG 220 Economics and Dynamics of Production 3 Units

Terms offered: Spring 2017, Spring 2016, Spring 2015 Analysis of the capacity and efficiency of production systems. Development of analytical tools for improving efficiency, customer service, and profitability of production environments. Design and development of effective industrial production planning systems. Modelling principles are illustrated by reviewing actual large-scale planning systems successfully implemented for naval ship overhaul and for semiconductor manufacturing. Economics and Dynamics of Production: Read More [+]

Prerequisites: 262A (may be taken concurrently), Mathematics 104 recommended

Fall and/or spring: 15 weeks - 3 hours of lecture per week

Additional Format: Three hours of Lecture per week for 15 weeks.

Instructor: Leachman

Economics and Dynamics of Production: Read Less [-]

IND ENG 221 Introduction to Financial Engineering 3 Units

Terms offered: Fall 2024, Spring 2024, Fall 2023 A course on financial concepts useful for engineers that will cover, among other topics, those of interest rates, present values, arbitrage, geometric Brownian motion, options pricing, & portfolio optimization. The Black-Scholes option-pricing formula will be derived and studied. Stochastic simulation ideas will be introduced and used to obtain the risk-neutral geometric Brownian motion values for certain types of Asian, barrier, and lookback options. Portfolio optimization problems will be considered both from a mean-variance and from a utility function point of view. Methods for evaluating real options will be presented. The use of mathematical optimization models as a framework for analyzing financial engineering problems will be shown. Introduction to Financial Engineering: Read More [+]

Prerequisites: 162 or 262A, course in probability, or consent of instructor

Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week

Additional Format: Three hours of lecture and one hour of discussion per week.

Instructors: Adler, Oren, Ross

Introduction to Financial Engineering: Read Less [-]

IND ENG 222 Financial Engineering Systems I 3 Units

Terms offered: Spring 2024, Spring 2023, Fall 2022 Introductory graduate level course, focusing on applications of operations research techniques, e.g., probability, statistics, and optimization, to financial engineering. The course starts with a quick review of 221, including no-arbitrage theory, complete market, risk-neutral pricing, and hedging in discrete model, as well as basic probability and statistical tools. It then covers Brownian motion, martingales, and Ito's calculus, and deals with risk-neutral pricing in continuous time models. Standard topics include Girsanov transformation, martingale representation theorem, Feyman-Kac formula, and American and exotic option pricings. Simulation techniques will be discussed at the end of the semester, and MATLAB (or C or S-Plus) will be used for computation. Financial Engineering Systems I: Read More [+]

Prerequisites: 221 or equivalent; 172 or Statistics 134 or a one-semester probability course

Additional Format: Three hours of Lecture and One hour of Discussion per week for 15 weeks.

Instructor: Guo

Financial Engineering Systems I: Read Less [-]

IND ENG 223 Financial Engineering Systems II 3 Units

Terms offered: Spring 2024, Spring 2023, Fall 2022 Advanced graduate course for Ph.D. students interested in pursuing a professional/research career in financial engineering. The course will start with a quick review of 222: the basics of Brownian motion, martingales, Ito's calculus, risk-neutral pricing in continuous time models. It then covers rigorously and in depth the most fundamental probability concepts for financial engineers, including stochastic integral, stochastic differential equations , and semi-martingales. The second half of the course will discuss the most recent topics in financial engineering, such as credit risk and analysis, risk measures and portfolio optimization, and liquidity risk and models. Financial Engineering Systems II: Read More [+]

Prerequisites: 222 or equivalent; 173 or 263A or equivalent

Financial Engineering Systems II: Read Less [-]

IND ENG 224 Portfolio and Risk Analytics 3 Units

Terms offered: Spring 2019, Spring 2018 The course aims to train students in hands-on statistical, optimization, and data analytics for quantitative portfolio and risk management. In addition, the course will introduce elements of financial markets and asset classes. The emphasis will be on computational methods such as variants of GARCH, Black-Litterman, conic optimization, Monte Carlo simulation for risk and optimization, factor modeling. Students will undertake computational assignments and a group project. They will also manage hypothetical portfolios throughout the course. Portfolio and Risk Analytics: Read More [+]

Prerequisites: A basic understanding of statistics and optimization, as well as fluency in a programming, language is required

Additional Format: Three hours of lecture per week.

Instructor: Alper Atamturk

Portfolio and Risk Analytics: Read Less [-]

IND ENG C227A Introduction to Convex Optimization 4 Units

Terms offered: Prior to 2007 The course covers some convex optimization theory and algorithms, and describes various applications arising in engineering design, machine learning and statistics, finance, and operations research. The course includes laboratory assignments, which consist of hands-on experience. Introduction to Convex Optimization: Read More [+]

Fall and/or spring: 15 weeks - 3 hours of lecture, 1 hour of discussion, and 2 hours of laboratory per week

Additional Format: Three hours of lecture and two hours of laboratory and one hour of discussion per week.

Instructors: El Ghaoui, Wainwright

Formerly known as: Electrical Engineering C227A/Industrial Engin and Oper Research C227A

Also listed as: EL ENG C227T

Introduction to Convex Optimization: Read Less [-]

IND ENG C227B Convex Optimization and Approximation 3 Units

Terms offered: Spring 2022, Spring 2021, Spring 2020, Spring 2019, Spring 2018, Spring 2017 Convex optimization as a systematic approximation tool for hard decision problems. Approximations of combinatorial optimization problems, of stochastic programming problems, of robust optimization problems (i.e., with optimization problems with unknown but bounded data), of optimal control problems. Quality estimates of the resulting approximation. Applications in robust engineering design, statistics , control, finance, data mining, operations research. Convex Optimization and Approximation: Read More [+]

Prerequisites: 227A or consent of instructor

Instructor: El Ghaoui

Also listed as: EL ENG C227C

Convex Optimization and Approximation: Read Less [-]

IND ENG 230 Economics of Supply Chains 3 Units

Terms offered: Spring 2024, Spring 2023 This course is geared towards understanding operational, strategic, and tactical aspects of supply chain man agement. Topics covered are from a broad range that includes demand modeling, inventory management, facility location as well as process flexibility, contracting, and auctions. Important models (both centralized and decentralized) for understanding the design, operation, and evaluation of supply chains will be discussed with the goal of developing a holistic understanding of supply chain management. Students will be exposed to the key concepts through a mixture of foundational theory and case studies from a variety of businesses. The course is intended for graduate students at the Masters level looking for a concrete introduction Economics of Supply Chains: Read More [+]

Prerequisites: Basics Optimization and Probability (IndEng 240, IndEng 241, or equivalent)

Instructor: Udwani

Economics of Supply Chains: Read Less [-]

IND ENG 231 Introduction to Data Modeling, Statistics, and System Simulation 3 Units

Terms offered: Spring 2023, Spring 2017, Spring 2015 This course uses simulation models for analyzing and optimizing systems where the underlying processes and/or parameters are not fully known, but data may be available, sampled, or artificially generated. Monte Carlo simulations are used in a weekly laboratory to model systems that may be too complex to approximate accurately with deterministic, stationary, or static models; and to measure the robustness of predictions and manage risks in decisions based on data-driven models. Introduction to Data Modeling, Statistics, and System Simulation: Read More [+]

Course Objectives: Students will understand the similarities and differences in methods for simulating the dynamics of complex, stochastic systems and apply these to model real systems. Special techniques for experimenting with computer simulations and analyzing the results will be used to understand the trade-offs in risk and performance in the presence of uncertainty.

Prerequisites: 262A, 263A or equivalents and some programming experience

Additional Format: Two hours of lecture and one hour of laboratory per week.

Instructors: Schruben, Guo, Lim

Introduction to Data Modeling, Statistics, and System Simulation: Read Less [-]

IND ENG 235 Applied Data Science with Venture Applications 3 Units

Terms offered: Spring 2023, Spring 2022, Fall 2021 This is an advanced project course in data science that offers a "maker" and/or "innovation" viewpoint. The course is focused first on developing an open-ended-real world project relating to data science. Related concepts of computer science tools and theoretical concepts are covered to support the project. These concepts include filtering, prediction, classification, LTI systems, and spectral analysis. After reviewing each concept, we explore implementing it in Python using libraries for math array functions, manipulation of tables, data architectures, natural language, and ML frameworks. Applied Data Science with Venture Applications: Read More [+]

Prerequisites: Prerequisites include: ability to write code in Python, and a probability or statistics course

Fall and/or spring: 15 weeks - 3 hours of lecture per week 15 weeks - 3 hours of lecture per week

Additional Format: Three hours of lecture per week. Three hours of lecture per week.

Instructor: Sidhu

Applied Data Science with Venture Applications: Read Less [-]

IND ENG 240 Optimization Analytics 3 Units

Terms offered: Fall 2024, Fall 2023, Fall 2022 Computing technology has advanced to the point that commonly available tools can be used to solve practical decision problems and optimize real-world systems quickly and efficiently. This course will focus on the understanding and use of such tools, to model and solve complex real-world business problems, to analyze the impact of changing data and relaxing assumptions on these decisions, and to understand the risks associated with particular decisions and outcomes. Optimization Analytics: Read More [+]

Prerequisites: Basic analysis and linear algebra, and basic computer skills and experience

Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of laboratory per week

Additional Format: Three hours of Lecture and One hour of Laboratory per week for 15 weeks.

Optimization Analytics: Read Less [-]

IND ENG 241 Risk Modeling, Simulation, and Data Analysis 3 Units

Terms offered: Fall 2024, Fall 2023, Fall 2022 This is a Masters of Engineering course, in which students will develop a fundamental understanding of how randomness and uncertainty are root causes of risk in modern enterprises. The technical material will be presented in the context of engineering team system design and operations decisions. Risk Modeling, Simulation, and Data Analysis: Read More [+]

Prerequisites: Basic notions of probability, statistics, and some programming and spreadsheet analysis experience

Risk Modeling, Simulation, and Data Analysis: Read Less [-]

IND ENG 242A Machine Learning and Data Analytics 4 Units

Terms offered: Fall 2024, Spring 2024 This course applies foundational concepts in programming, databases, machine learning, and statistical modeling to answer questions from business and social science. The goal is for students to develop the experience and intuition to gather and build new datasets and answer substantive questions. Machine Learning and Data Analytics: Read More [+]

Prerequisites: Prerequisites include working knowledge of a programming language (preferably Python), database language (preferably SQL), a statistical package (preferably R), and an understanding of basic linear and non-­‐linear statistical models. Prior exposure to machine learning is helpful, though this will be covered in the predictive analytics and theory course

Credit Restrictions: Students will receive no credit for IND ENG 242A after completing IND ENG 142 .

Instructor: Grigas

Formerly known as: Industrial Engin and Oper Research 242

Machine Learning and Data Analytics: Read Less [-]

IND ENG 242B Machine Learning and Data Analytics II 4 Units

Terms offered: Spring 2024 Following IEOR 142A/242A, this course further introduces students to essential methodologies and recent trends in machine learning and data analytics. The course will bridge theoretical foundations with applied data analytics by using examples and real datasets from domains such as e-commerce, social media, finance, and more. Students will gain experience with various data analytics packages in Python and will deliver a comprehensive team project. Topics include: deep learning, time series and survival analysis, end-to-end learning, causal inference, reinforcement learning, and ethics, fairness and safety in artificial intelligence. Machine Learning and Data Analytics II: Read More [+]

Prerequisites: IndEng 142A or IndEng 242A or equivalent introductory machine learning class. Familiarity with the Python programming language

Credit Restrictions: Students will receive no credit for IND ENG 242B after completing IND ENG 142B .

Machine Learning and Data Analytics II: Read Less [-]

IND ENG 243 Analytics Lab 4 Units

Terms offered: Spring 2024, Spring 2023, Spring 2022 A project course to provide hands-on experience in end-to-end analytics development from exploratory analytics to systems analytics in an industry context, including communication of recommendations. Students will work in teams on projects and build solutions to business/industry challenges using Python packages such as Pandas, NumPy, Matplotlib, scikit- learn, Bokeh, and relevant optimization and simulation software. Analytics Lab: Read More [+]

Student Learning Outcomes: Learning goals include technical communication and project presentation.

Prerequisites: IEOR 240 Optimization Analytics, IEOR 241 Risk Modeling & Simulation Analytics, IEOR 242 Applications in Data Analysis. Familiarity with the Python programming language is also expected

Instructors: Aswani, Grigas

Analytics Lab: Read Less [-]

IND ENG 245 Fundamentals of Revenue Management 3 Units

Terms offered: Fall 2024, Fall 2023 This course will introduce students to the science of engineering demand given a fixed supply of various goods and services when the customer base is heterogeneous and uncertain (a.k.a. Revenue Management). This requires an understanding of customer choice behaviour, different pricing and allocation strategies, and mechanisms for customer and seller interaction. The course will focus on introducing students to (i) Models that capture the key dynamics of these problems and (ii) Algorithmic ideas that turn these models into actionable decisions. The broad usefulness of concepts covered will be demonstrated through several applications such as in airline reservation systems, retail, advertising, e-commerce as well as non-profit applications. Fundamentals of Revenue Management: Read More [+]

Prerequisites: INDENG 240 and INDENG 241 or equivalent

Credit Restrictions: Students will receive no credit for IND ENG 245 after completing IND ENG 145 .

Fundamentals of Revenue Management: Read Less [-]

IND ENG 248 Supply Chain Innovation, Strategy, and Analytics 3 Units

Terms offered: Fall 2013 This course introduces you to the field of supply chain management through a series of lectures and case studies that emphasize innovative concepts in supply chain management that have proven to be beneficial for a good number of adopters. Innovations that we will discuss include collaborative forecasting, social media, online procurement, and technologies such as RFID. Supply Chain Innovation, Strategy, and Analytics: Read More [+]

Prerequisites: Introductory course on Production and Inventory Control or Operations Management

Supply Chain Innovation, Strategy, and Analytics: Read Less [-]

IND ENG 250 Introduction to Production Planning and Logistics Models 3 Units

Terms offered: Fall 2024, Fall 2023, Fall 2022 This will be an introductory first-year graduate course covering fundamental models in production planning and logistics. Models, algorithms, and analytical techniques for inventory control, production scheduling, production planning, facility location and logistics network design, vehicle routing, and demand forecasting will be discussed. Introduction to Production Planning and Logistics Models: Read More [+]

Prerequisites: 262A and 263A taken concurrently

Instructor: Kaminsky

Introduction to Production Planning and Logistics Models: Read Less [-]

IND ENG 251 Facilities Design and Logistics 3 Units

Terms offered: Fall 2012, Spring 2005, Spring 2004 Design and analysis of models and algorithms for facility location, vehicle routing, and facility layout problems. Emphasis will be placed on both the use of computers and the theoretical analysis of models and algorithms. Facilities Design and Logistics: Read More [+]

Prerequisites: 262A, and either 172 or Statistics 134

Facilities Design and Logistics: Read Less [-]

IND ENG 252 Service Operations Management 3 Units

Terms offered: Spring 2021, Spring 2014, Spring 2013 This course focuses on the design of service businesses such as commercial banks, hospitals, airline companies, call centers, restaurants, Internet auction websites, and information providers. The material covered in the course includes internet auctions, procurement, service facility location, sevice quality management, capacity planning, airline ticket pricing, financial plan design, pricing of digital goods, call center management, service competition, revenue management in queueing systems, information intermediaries, and health care. The goal of the instructors is to equip the students with sufficient technical background to be able to do research in this area. Service Operations Management: Read More [+]

Prerequisites: Students who have not advanced to M.S., M.S./Ph.D., or Ph.D. levels or are not in the Industrial Engineering and Operations Research Department must consult with the instructor before taking this course for credit

Instructors: Shen, Chen

Service Operations Management: Read Less [-]

IND ENG 253 Supply Chain Operation and Management 3 Units

Terms offered: Spring 2013, Spring 2012, Spring 2011 Supply chain analysis is the study of quantitative models that characterize various economic trade-offs in the supply chain. The field has made significant strides on both theoretical and practical fronts. On the theoretical front, supply chain analysis inspires new research ventures that blend operations research, game theory, and microeconomics. These ventures result in an unprecedented amalgamation of prescriptive, descriptive, and predictive models characteristic of each subfield. On the practical front, supply chain analysis offers solid foundations for strategic positioning, policy setting, and decision making. Supply Chain Operation and Management: Read More [+]

Repeat rules: Course may be repeated for credit without restriction.

Instructor: Shen

Supply Chain Operation and Management: Read Less [-]

IND ENG C253 Supply Chain and Logistics Management 3 Units

Terms offered: Spring 2024, Spring 2023, Spring 2022, Spring 2021 Supply chain analysis is the study of quantitative models that characterize various economic trade-offs in the supply chain. The field has made significant strides on both theoretical and practical fronts. On the theoretical front, supply chain analysis inspires new research ventures that blend operations research, game theory, and microeconomics. These ventures result in an unprecedented amalgamation of prescriptive, descriptive , and predictive models characteristic of each subfield. On the practical front, supply chain analysis offers solid foundations for strategic positioning, policy setting, and decision making. Supply Chain and Logistics Management: Read More [+]

Also listed as: CIV ENG C258

Supply Chain and Logistics Management: Read Less [-]

IND ENG 254 Production and Inventory Systems 3 Units

Terms offered: Spring 2014, Fall 2011, Fall 2009 Mathematical and computer methods for design, planning, scheduling, and control in manufacturing and distribution systems. Production and Inventory Systems: Read More [+]

Prerequisites: 262A or 150; 263A or 173 recommended

Production and Inventory Systems: Read Less [-]

IND ENG 255 Frontiers in Revenue Management 3 Units

Terms offered: Spring 2024, Spring 2023, Spring 2022 This course is targeted at understanding RM problems in the booming environment of online platforms and marketplaces with applications ranging from online advertising to ride-sharing markets. The main focus is on design and analysis of models and algorithms for matching, pricing, incentivizing, and personalizing on such platforms. Sample topics include, but are not limited to, resource allocation and pricing under uncertain sequential demand , mechanism design, discrete choice models, static and dynamic assortment optimization, real-time recommendations, spatial supply response and supply re-balancing in bike/ride sharing systems. Frontiers in Revenue Management: Read More [+]

Prerequisites: IndEng 262A and IndEng 263A (or equivalent coursework) IndEng 264 and IndEng 269 recommended but not required

Frontiers in Revenue Management: Read Less [-]

IND ENG 256 Heathcare Analytics 3 Units

Terms offered: Spring 2024 With the growing complexity of providing healthcare, it is increasingly important to design and manage health systems using engineering and analytics perspectives. This course will cover topics related to healthcare analytics, including: optimizing chronic disease management, designing matching markets for health systems, developing predictive analytics models, and managing resource utilization. Heathcare Analytics: Read More [+]

Prerequisites: Courses in mathematical modeling (such as IND ENG 160 and IND ENG 172 ) and computer programming (such as CS C8 or CS 61A) are recommended

Credit Restrictions: Students will receive no credit for IND ENG 256 after completing IND ENG 156 .

Instructor: Aswani

Heathcare Analytics: Read Less [-]

IND ENG 258 Control and Optimization for Power Systems 3 Units

Terms offered: Spring 2019, Spring 2017 One of the grand challenges of this century is the modernization of electrical power networks. This graduate-level course provides a fundamental understanding of the mathematics behind the operation of power grids. Control and Optimization for Power Systems: Read More [+]

Course Objectives: Students will understand the operation of power networks from a control and optimization perspective. They will learn how mathematical tools and computational methods are used for the design, modeling, planning, and real-time operation of power grids. They will also learn about the interaction between operation and electricity market.

Instructor: Lavaei

Control and Optimization for Power Systems: Read Less [-]

IND ENG 261 Experimenting with Simulated Systems 3 Units

Terms offered: Spring 2009, Spring 2007, Spring 2006 This course will introduce graduate and upper division undergraduate students to modern methods for simulating discrete event models of complex stochastic systems. About a third of the course will be devoted to system modeling, with the remaining two-thirds concentrating on simulation experimental design and analysis. Experimenting with Simulated Systems: Read More [+]

Prerequisites: 165 or equivalent statistics course, and some computer programming background

Instructors: Ross, Schruben, Shanthikumar

Experimenting with Simulated Systems: Read Less [-]

IND ENG 262A Mathematical Programming I 4 Units

Terms offered: Fall 2024, Fall 2023, Fall 2022 Basic graduate course in linear programming and introduction to network flows and non-linear programming. Formulation and model building. The simplex method and its variants. Duality theory. Sensitivity analysis, parametric programming, convergence (theoretical and practical). Polynomial time algorithms. Introduction to network flows models. Optimality conditions for non linear optimization problems. Mathematical Programming I: Read More [+]

Prerequisites: Mathematics 110

Instructors: Adler, Oren

Mathematical Programming I: Read Less [-]

IND ENG 262B Mathematical Programming II 3 Units

Terms offered: Spring 2024, Spring 2023, Spring 2022 Basic first year graduate course in optimization of non-linear programs. Formulation and model building. Theory of optimization for constrained and unconstrained problems. Study of algorithms for non-linear optimization with emphasis on design considerations and performance evaluation. Mathematical Programming II: Read More [+]

Prerequisites: Math 110 or equivalent

Mathematical Programming II: Read Less [-]

IND ENG 263A Applied Stochastic Process I 4 Units

Terms offered: Fall 2024, Fall 2023, Fall 2022 Conditional Expectation. Poisson and general point process and renewal theory. Renewal reward processes with application to inventory, congestion, and replacement models. Discrete and continuous time Markov chains; with applications to various stochastic systems--such as queueing systems, inventory models and reliability systems. Applied Stochastic Process I: Read More [+]

Prerequisites: Industrial Engineering 172, or Statistics 134 or Statistics 200A.  Probability background with Industrial Engineering 173 or equivalent is recommended

Instructor: Righter

Applied Stochastic Process I: Read Less [-]

IND ENG 263B Applied Stochastic Process II 3 Units

Terms offered: Spring 2024, Spring 2023, Spring 2022 Continuous time Markov chains. The reversed chain concept in continuous time Markov chains with applications of queueing theory. Semi-Markov processes with emphasis on application. Brownian Motion. Random walks with applications. Introduction to Martinjales. Applied Stochastic Process II: Read More [+]

Prerequisites: 263A

Applied Stochastic Process II: Read Less [-]

IND ENG 264 Computational Optimization 3 Units

Terms offered: Spring 2017, Spring 2016, Spring 2015 This course is on computational methods for the solution of large-scale optimization problems. The focus is on converting the theory of optimization into effective computational techniques. Course topics include an introduction to polyhedral theory, cutting plane methods, relaxation, decomposition and heuristic approaches for large-scale optimization problems. Computational Optimization: Read More [+]

Prerequisites: 262A

Instructor: Atamturk

Computational Optimization: Read Less [-]

IND ENG 265 Learning and Optimization 3 Units

Terms offered: Spring 2022, Fall 2021, Spring 2021 This course will cover topics related to the interplay between optimization and statistical learning. The first part of the course will cover statistical modeling procedures that can be defined as the minimizer of a suitable optimization problem. The second part of the course will discuss the formulation and numerical implementation of learning-based model predictive control (LBMPC), which is a method for robust adaptive optimization that can use machine learning to provide the adaptation. The last part of the course will deal with inverse decision-making problems, which are problems where an agent's decisions are observed and used to infer properties about the agent. Learning and Optimization: Read More [+]

Prerequisites: Course on optimization (Industrial Engineering 162 or equivalent); course on statistics or stochastic processes (Industrial Engineering 165 or equivalent) Industrial Engin and Oper Research 165

Learning and Optimization: Read Less [-]

IND ENG 266 Network Flows and Graphs 3 Units

Terms offered: Fall 2024, Spring 2024, Fall 2022 Survey of solution techniques and problems that have formulations in terms of flows in networks. Max-flow min-cut theorem. Minimum cost flows. Multiterminal and multicommodity flows. Relationship with linear programming, transportation problems, electrical networks and critical path scheduling. Network Flows and Graphs: Read More [+]

Prerequisites: 262A (may be taken concurrently)

Instructors: Adler, Hochbaum

Network Flows and Graphs: Read Less [-]

IND ENG 267 Queueing Theory 3 Units

Terms offered: Spring 2022, Spring 2016, Spring 2015 The result "L = (lambda) w" and other conservation laws. Elementary queueing models; comparing single- and multiple-server queues. PASTA. Work. Markovian queues; product form results. Overflow models. Embedded Markov chains. Random walks and the GI/G/l queues. Work conservation; priorities. Bounds and approximations. Queueing Theory: Read More [+]

Prerequisites: IND ENG 263A

Queueing Theory: Read Less [-]

IND ENG 268 Applied Dynamic Programming 3 Units

Terms offered: Fall 2024, Fall 2021, Spring 2018 Dynamic programming formulation of deterministic decision process problems, analytical and computational methods of solution, application to problems of equipment replacement, resource allocation, scheduling, search and routing. Brief introduction to decision making under risk and uncertainty. Applied Dynamic Programming: Read More [+]

Prerequisites: Mathematics 51

Instructor: Dreyfus

Applied Dynamic Programming: Read Less [-]

IND ENG 269 Integer Programming and Combinatorial Optimization 3 Units

Terms offered: Spring 2020, Spring 2010, Spring 2009 The course deals with discrete optimization problems and their complexity. These topics include complexity analysis of algorithms and its drawbacks; solving a system of linear integer equations and inequalities; strongly polynomial algorithms, network flow problems (including matching and branching); polyhedral optimization; branch and bound and lagrangean relaxation. Integer Programming and Combinatorial Optimization: Read More [+]

Instructor: Hochbaum

Integer Programming and Combinatorial Optimization: Read Less [-]

IND ENG 270 Current Readings in Innovation 3 Units

Terms offered: Fall 2015, Fall 2014 This seminar and discussion class aims to survey current and classic research on innovation and help doctoral students formulate their research designs. Readings are drawn from economics, organizations, and other social sciences, and engineering and in particular, data science research on analyzing large data sets. Students develop research designs and present each week and formally for their final. A written paper is also required. Authors join us, physically or virtually. Current Readings in Innovation: Read More [+]

Prerequisites: Background: upper level standing or graduate student, any school

Repeat rules: Course may be repeated for credit when topic changes.

Fall and/or spring: 15 weeks - 3 hours of seminar per week

Additional Format: Three hours of seminar per week.

Instructors: Fleming, Lee

Current Readings in Innovation: Read Less [-]

IND ENG 280 Systems Analysis and Design Project 3 Units

Terms offered: Spring 2011, Spring 2010, Spring 2009 A project course for students interested in applications of operations research and engineering methods. One or more systems, which may be public or in the private sector, will be selected for detailed analysis and re-designed by student groups. Systems Analysis and Design Project: Read More [+]

Prerequisites: 262A, 263A

Systems Analysis and Design Project: Read Less [-]

IND ENG 288 Automation Science and Engineering 3 Units

Terms offered: Prior to 2007 Automation is a central aspect of contemporary industrial engineering that combines sensors, actuators, and computing to monitor and perform operations. It is applied to a broad range of applications from manufacturing to transporation to healthcare. This course provides an introduction to analysis, models, algorithms, research, and practical skills in the field and includes a laboratory component where students will learn and apply basic skills in computer programming and interfacing of sensors and motors that will culminate in a team design project. Automation Science and Engineering: Read More [+]

Fall and/or spring: 15 weeks - 2 hours of lecture, 1 hour of discussion, and 1 hour of laboratory per week

Additional Format: Two hours of Lecture, One hour of Discussion, and One hour of Laboratory per week for 15 weeks.

Automation Science and Engineering: Read Less [-]

IND ENG 290 Special Topics in Industrial Engineering and Operation Research 2 - 3 Units

Terms offered: Spring 2024, Fall 2023, Spring 2023 Lectures and appropriate assignments on fundamental or applied topics of current interest in industrial engineering and operations research. Special Topics in Industrial Engineering and Operation Research: Read More [+]

Prerequisites: Upper level standing or graduate student

Fall and/or spring: 15 weeks - 2-3 hours of lecture per week

Summer: 6 weeks - 5-7.5 hours of lecture per week 10 weeks - 3-4.5 hours of lecture per week

Additional Format: Two to three hours of lecture per week. Three to four and one-half hours of lecture per week for 10 weeks. Five to seven and one-half hours of lecture per week for 6 weeks.

Special Topics in Industrial Engineering and Operation Research: Read Less [-]

IND ENG 290A Dynamic Production Theory and Planning Models 3 Units

Terms offered: Spring 2014, Fall 2008, Spring 2008 Development of dynamic activity analysis models for production planning and scheduling. Relationship to theory of production, inventory theory and hierarchical organization of production management. Dynamic Production Theory and Planning Models: Read More [+]

Prerequisites: 220 and 254

Dynamic Production Theory and Planning Models: Read Less [-]

IND ENG 290G Advanced Mathematical Programming 3 Units

Terms offered: Spring 2017, Spring 2014, Spring 2011 Selected topics in mathematical programming. The actual subjects covered may include: Convex analysis, duality theory, complementary pivot theory, fixed point theory, optimization by vector space methods, advanced topics in nonlinear algorithms, complexity of mathematical programming algorithms (including linear programming). Advanced Mathematical Programming: Read More [+]

Advanced Mathematical Programming: Read Less [-]

IND ENG 290R Topics in Risk Theory 3 Units

Terms offered: Spring 2016, Spring 2015, Spring 2014 Seminar on selected topics from financial and technological risk theory, such as risk modeling, attitudes towards risk and utility theory, portfolio management, gambling and speculation, insurance and other risk-sharing arrangements, stochastic models of risk generation and run off, risk reserves, Bayesian forecasting and credibility approximations, influence diagrams, decision trees. Topics will vary from year to year. Topics in Risk Theory: Read More [+]

Topics in Risk Theory: Read Less [-]

IND ENG 298 Group Studies, Seminars, or Group Research 1 - 4 Units

Terms offered: Fall 2024, Spring 2024, Fall 2023 Advanced seminars in industrial engineering and operations research. Group Studies, Seminars, or Group Research: Read More [+]

Fall and/or spring: 15 weeks - 1-4 hours of colloquium per week

Additional Format: One to four hours of colloquium per week.

Grading: The grading option will be decided by the instructor when the class is offered.

Group Studies, Seminars, or Group Research: Read Less [-]

IND ENG 299 Individual Study or Research 1 - 12 Units

Terms offered: Fall 2024, Summer 2024 Second 6 Week Session, Fall 2023 Individual investigation of advanced industrial engineering problems. Individual Study or Research: Read More [+]

Fall and/or spring: 15 weeks - 3-36 hours of independent study per week

Summer: 6 weeks - 7.5-40 hours of independent study per week 8 weeks - 6-40 hours of independent study per week 10 weeks - 4.5-40 hours of independent study per week

Additional Format: Individual conferences. Forty-five hours of work per unit per term.

Grading: Offered for satisfactory/unsatisfactory grade only.

Individual Study or Research: Read Less [-]

IND ENG 375 GSI Proseminar on Teaching Engineering 2 Units

Terms offered: Fall 2024, Fall 2023, Fall 2022 This course provides basic training for graduate student instructors (GSIs). Discussion, practice, and review of fundamentals, issues, and best practices in teaching for any engineering course. Topics include: preparing a syllabus; public speaking and coping with language barriers; creating effective slides and exams; differing student learning styles; grading; encouraging diversity, equity, and inclusion; ethics; dealing with conflict and misconduct; and other topics relevant to serving as an effective teaching assistant. GSI Proseminar on Teaching Engineering: Read More [+]

Course Objectives: 2. Organize concepts and objectives covered in an engineering course. 3. Design activities and discussions to promote learning and provide practice in course concepts and objectives. 4. Integrate verbal and visual methods of conveying engineering concepts and practices in the classroom and in discussions. 5. Practice fair and helpful evaluation of student work. After completion of the course, GSIs will be able to perform the following course-related tasks: 1. Understand the University policies and procedures on academic integrity and ethics.

Prerequisites: Graduate Standing or ASE (Academic Student Employee) Status

Fall and/or spring: 15 weeks - 2 hours of seminar per week

Additional Format: Two hours of seminar per week.

Subject/Course Level: Industrial Engin and Oper Research/Professional course for teachers or prospective teachers

GSI Proseminar on Teaching Engineering: Read Less [-]

IND ENG 601 Individual Study for Master's Students 1 - 12 Units

Terms offered: Fall 2010, Fall 2008, Spring 2008 Individual study for the comprehensive in consultation with the field adviser. Units may not be used to meet either unit or residence requirements for a master's degree. Individual Study for Master's Students: Read More [+]

Fall and/or spring: 15 weeks - 0 hours of independent study per week

Summer: 8 weeks - 6-68 hours of independent study per week

Additional Format: Forty-five hours of work per unit per term. Individual conferences.

Subject/Course Level: Industrial Engin and Oper Research/Graduate examination preparation

Individual Study for Master's Students: Read Less [-]

IND ENG 602 Individual Study for Doctoral Students 1 - 12 Units

Terms offered: Fall 2010, Spring 2008, Fall 2007 Individual study in consultation with the major field adviser, intended to provide an opportunity for qualified students to prepare themselves for the various examinations required of candidates for the Ph.D. (and other doctoral degrees). May not be used for unit or residence requirements for the doctoral degree. Individual Study for Doctoral Students: Read More [+]

Individual Study for Doctoral Students: Read Less [-]

Contact Information

Department of industrial engineering and operations research.

4141 Etcheverry Hall

Phone: 510-642-5484

Department Chair, Program Director of the Master of Analytics

Alper Atamturk

4143 Etcheverry Hall

[email protected]

Head Graduate Advisor, IEOR MS & PhD

Rhonda Righter

4187 Etcheverry Hall

[email protected]

Head Graduate Advisor, IEOR MEng

4183 Etcheverry Hall

[email protected]

IEOR Graduate Student Services

Heather Iwata and Erica Diffenderfer

[email protected].

IEOR Admissions

[email protected]

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Top 150 Mechanical Engineering Research Topics [Updated]

Mechanical engineering is an intriguing discipline that holds significant sway in shaping our world. With a focus on crafting inventive machinery and fostering sustainable energy initiatives, mechanical engineers stand as pioneers in driving technological progress. However, to make meaningful contributions to the field, researchers must carefully choose their topics of study. In this blog, we’ll delve into various mechanical engineering research topics, ranging from fundamental principles to emerging trends and interdisciplinary applications.

How to Select Mechanical Engineering Research Topics?

Table of Contents

Selecting the right mechanical engineering research topics is crucial for driving impactful innovation and addressing pressing challenges. Here’s a step-by-step guide to help you choose the best research topics:

• Identify Your Interests: Start by considering your passions and areas of expertise within mechanical engineering. What topics excite you the most? Choosing a subject that aligns with your interests will keep you motivated throughout the research process.
• Assess Current Trends: Stay updated on the latest developments and trends in mechanical engineering. Look for emerging technologies, pressing industry challenges, and areas with significant research gaps. These trends can guide you towards relevant and timely research topics.
• Conduct Literature Review: Dive into existing literature and research papers within your field of interest. Identify gaps in knowledge, unanswered questions, or areas that warrant further investigation. Building upon existing research can lead to more impactful contributions to the field.
• Consider Practical Applications: Evaluate the practical implications of potential research topics. How will your research address real-world problems or benefit society? Choosing topics with tangible applications can increase the relevance and impact of your research outcomes.
• Consult with Advisors and Peers: Seek guidance from experienced mentors, advisors, or peers in the field of mechanical engineering. Discuss your research interests and potential topics with them to gain valuable insights and feedback. Their expertise can help you refine your ideas and select the most promising topics.
• Define Research Objectives: Clearly define the objectives and scope of your research. What specific questions do you aim to answer or problems do you intend to solve? Establishing clear research goals will guide your topic selection process and keep your project focused.
• Consider Resources and Constraints: Take into account the resources, expertise, and time available for your research. Choose topics that are feasible within your constraints and align with your available resources. Balancing ambition with practicality is essential for successful research endeavors.
• Brainstorm and Narrow Down Options: Generate a list of potential research topics through brainstorming and exploration. Narrow down your options based on criteria such as relevance, feasibility, and alignment with your interests and goals. Choose the most promising topics that offer ample opportunities for exploration and discovery.
• Seek Feedback and Refinement: Once you’ve identified potential research topics, seek feedback from colleagues, advisors, or experts in the field. Refine your ideas based on their input and suggestions. Iteratively refining your topic selection process will lead to a more robust and well-defined research proposal.
• Stay Flexible and Open-Minded: Remain open to new ideas and opportunities as you progress through the research process. Be willing to adjust your research topic or direction based on new insights, challenges, or discoveries. Flexibility and adaptability are key qualities for successful research endeavors in mechanical engineering.

By following these steps and considering various factors, you can effectively select mechanical engineering research topics that align with your interests, goals, and the needs of the field.

Top 50 Mechanical Engineering Research Topics For Beginners

• Analysis of the efficiency of different heat exchanger designs.
• Optimization of airfoil shapes for enhanced aerodynamic performance.
• Investigation of renewable energy harvesting using piezoelectric materials.
• Development of smart materials for adaptive structures in aerospace applications.
• Study of vibration damping techniques for improving vehicle ride comfort.
• Design and optimization of suspension systems for off-road vehicles.
• Analysis of fluid flow characteristics in microchannels for cooling electronics.
• Evaluation of the performance of different brake systems in automotive vehicles.
• Development of lightweight materials for automotive and aerospace industries.
• Investigation of the effects of friction stir welding parameters on joint properties.
• Design and testing of a small-scale wind turbine for rural electrification.
• Study of the dynamics of flexible multibody systems in robotics.
• Development of a low-cost prosthetic limb using 3D printing technology.
• Analysis of heat transfer in electronic packaging for thermal management.
• Investigation of energy harvesting from vehicle suspension systems.
• Design and optimization of heat sinks for electronic cooling applications.
• Study of material degradation in composite structures under various loading conditions.
• Development of bio-inspired robotic mechanisms for locomotion.
• Investigation of the performance of regenerative braking systems in electric vehicles.
• Design and analysis of an autonomous agricultural robot for crop monitoring.
• Optimization of gas turbine blade profiles for improved efficiency.
• Study of the aerodynamics of animal-inspired flying robots (bio-drones).
• Development of advanced control algorithms for robotic manipulators.
• Analysis of wear mechanisms in mechanical components under different operating conditions.
• Investigation of the efficiency of solar water heating systems.
• Design and optimization of microfluidic devices for biomedical applications.
• Study of the effects of additive manufacturing parameters on part quality.
• Development of assistive devices for individuals with disabilities.
• Analysis of the performance of different types of bearings in rotating machinery.
• Investigation of the feasibility of using shape memory alloys in actuator systems.
• Design and optimization of a compact heat exchanger for space applications.
• Study of the effects of surface roughness on friction and wear in sliding contacts.
• Development of energy-efficient HVAC systems for buildings.
• Analysis of the performance of different types of fuel cells for power generation.
• Investigation of the feasibility of using biofuels in internal combustion engines.
• Design and testing of a micro-scale combustion engine for portable power generation.
• Study of the mechanics of soft materials for biomedical applications.
• Development of exoskeletons for rehabilitation and assistance in mobility.
• Analysis of the effects of vehicle aerodynamics on fuel consumption.
• Investigation of the potential of ocean wave energy harvesting technologies.
• Design and optimization of energy-efficient refrigeration systems.
• Study of the dynamics of flexible structures subjected to dynamic loads.
• Development of sensors and actuators for structural health monitoring.
• Analysis of the performance of different cooling techniques in electronics.
• Investigation of the potential of hydrogen fuel cells for automotive applications.
• Design and testing of a small-scale hydroelectric power generator.
• Study of the mechanics of cellular materials for impact absorption.
• Development of unmanned aerial vehicles (drones) for environmental monitoring.
• Analysis of the efficiency of different propulsion systems in space exploration.
• Investigation of the potential of micro-scale energy harvesting technologies for powering wireless sensors.

Top 50 Mechanical Engineering Research Topics For Intermediate

• Optimization of heat exchanger designs for enhanced energy efficiency.
• Investigating the effects of surface roughness on fluid flow in microchannels.
• Development of lightweight materials for automotive applications.
• Modeling and simulation of combustion processes in internal combustion engines.
• Design and analysis of novel wind turbine blade configurations.
• Study of advanced control strategies for unmanned aerial vehicles (UAVs).
• Analysis of wear and friction in mechanical components under varying operating conditions.
• Investigation of thermal management techniques for high-power electronic devices.
• Development of smart materials for shape memory alloys in actuator applications.
• Design and fabrication of microelectromechanical systems (MEMS) for biomedical applications.
• Optimization of additive manufacturing processes for metal 3D printing.
• Study of fluid-structure interaction in flexible marine structures.
• Analysis of fatigue behavior in composite materials for aerospace applications.
• Development of energy harvesting technologies for sustainable power generation.
• Investigation of bio-inspired robotics for locomotion in challenging environments.
• Study of human factors in the design of ergonomic workstations.
• Design and control of soft robots for delicate manipulation tasks.
• Development of advanced sensor technologies for condition monitoring in rotating machinery.
• Analysis of aerodynamic performance in hypersonic flight vehicles.
• Study of regenerative braking systems for electric vehicles.
• Optimization of cooling systems for high-performance computing (HPC) applications.
• Investigation of fluid dynamics in microfluidic devices for lab-on-a-chip applications.
• Design and optimization of passive and active vibration control systems.
• Analysis of heat transfer mechanisms in nanofluids for thermal management.
• Development of energy-efficient HVAC (heating, ventilation, and air conditioning) systems.
• Study of biomimetic design principles for robotic grippers and manipulators.
• Investigation of hydrodynamic performance in marine propeller designs.
• Development of autonomous agricultural robots for precision farming.
• Analysis of wind-induced vibrations in tall buildings and bridges.
• Optimization of material properties for additive manufacturing of aerospace components.
• Study of renewable energy integration in smart grid systems.
• Investigation of fracture mechanics in brittle materials for structural integrity assessment.
• Development of wearable sensors for human motion tracking and biomechanical analysis.
• Analysis of combustion instability in gas turbine engines.
• Optimization of thermal insulation materials for building energy efficiency.
• Study of fluid-structure interaction in flexible wing designs for unmanned aerial vehicles.
• Investigation of heat transfer enhancement techniques in heat exchanger surfaces.
• Development of microscale actuators for micro-robotic systems.
• Analysis of energy storage technologies for grid-scale applications.
• Optimization of manufacturing processes for lightweight automotive structures.
• Study of tribological behavior in lubricated mechanical systems.
• Investigation of fault detection and diagnosis techniques for industrial machinery.
• Development of biodegradable materials for sustainable packaging applications.
• Analysis of heat transfer in porous media for thermal energy storage.
• Optimization of control strategies for robotic manipulation tasks in uncertain environments.
• Study of fluid dynamics in fuel cell systems for renewable energy conversion.
• Investigation of fatigue crack propagation in metallic alloys.
• Development of energy-efficient propulsion systems for unmanned underwater vehicles (UUVs).
• Analysis of airflow patterns in natural ventilation systems for buildings.
• Optimization of material selection for additive manufacturing of biomedical implants.

Top 50 Mechanical Engineering Research Topics For Advanced

• Development of advanced materials for high-temperature applications
• Optimization of heat exchanger design using computational fluid dynamics (CFD)
• Control strategies for enhancing the performance of micro-scale heat transfer devices
• Multi-physics modeling and simulation of thermoelastic damping in MEMS/NEMS devices
• Design and analysis of next-generation turbofan engines for aircraft propulsion
• Investigation of advanced cooling techniques for electronic devices in harsh environments
• Development of novel nanomaterials for efficient energy conversion and storage
• Optimization of piezoelectric energy harvesting systems for powering wireless sensor networks
• Investigation of microscale heat transfer phenomena in advanced cooling technologies
• Design and optimization of advanced composite materials for aerospace applications
• Development of bio-inspired materials for impact-resistant structures
• Exploration of advanced manufacturing techniques for producing complex geometries in aerospace components
• Integration of artificial intelligence algorithms for predictive maintenance in rotating machinery
• Design and optimization of advanced robotics systems for industrial automation
• Investigation of friction and wear behavior in advanced lubricants for high-speed applications
• Development of smart materials for adaptive structures and morphing aircraft wings
• Exploration of advanced control strategies for active vibration damping in mechanical systems
• Design and analysis of advanced wind turbine blade designs for improved energy capture
• Investigation of thermal management solutions for electric vehicle batteries
• Development of advanced sensors for real-time monitoring of structural health in civil infrastructure
• Optimization of additive manufacturing processes for producing high-performance metallic components
• Investigation of advanced corrosion-resistant coatings for marine applications
• Design and analysis of advanced hydraulic systems for heavy-duty machinery
• Exploration of advanced filtration technologies for water purification and wastewater treatment
• Development of advanced prosthetic limbs with biomimetic functionalities
• Investigation of microscale fluid flow phenomena in lab-on-a-chip devices for medical diagnostics
• Optimization of heat transfer in microscale heat exchangers for cooling electronics
• Development of advanced energy-efficient HVAC systems for buildings
• Exploration of advanced propulsion systems for space exploration missions
• Investigation of advanced control algorithms for autonomous vehicles in complex environments
• Development of advanced surgical robots for minimally invasive procedures
• Optimization of advanced suspension systems for improving vehicle ride comfort and handling
• Investigation of advanced materials for 3D printing in aerospace manufacturing
• Development of advanced thermal barrier coatings for gas turbine engines
• Exploration of advanced wear-resistant coatings for cutting tools in machining applications
• Investigation of advanced nanofluids for enhanced heat transfer in cooling applications
• Development of advanced biomaterials for tissue engineering and regenerative medicine
• Exploration of advanced actuators for soft robotics applications
• Investigation of advanced energy storage systems for grid-scale applications
• Development of advanced rehabilitation devices for individuals with mobility impairments
• Exploration of advanced materials for earthquake-resistant building structures
• Investigation of advanced aerodynamic concepts for reducing drag and improving fuel efficiency in vehicles
• Development of advanced microelectromechanical systems (MEMS) for biomedical applications
• Exploration of advanced control strategies for unmanned aerial vehicles (UAVs)
• Investigation of advanced materials for lightweight armor systems
• Development of advanced prosthetic interfaces for improving user comfort and functionality
• Exploration of advanced algorithms for autonomous navigation of underwater vehicles
• Investigation of advanced sensors for detecting and monitoring air pollution
• Development of advanced energy harvesting systems for powering wireless sensor networks
• Exploration of advanced concepts for next-generation space propulsion systems.

Mechanical engineering research encompasses a wide range of topics, from fundamental principles to cutting-edge technologies and interdisciplinary applications. By choosing the right mechanical engineering research topics and addressing key challenges, researchers can contribute to advancements in various industries and address pressing global issues. As we look to the future, the possibilities for innovation and discovery in mechanical engineering are endless, offering exciting opportunities to shape a better world for generations to come.

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• Interest Areas & Applications

Human Factors/Ergonomics

Manufacturing, operations research, operations, services, and analytics.

• Faculty Research Interests
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The Harold and Inge Marcus Department of Industrial and Manufacturing Engineering supports research efforts in four areas of interest and several applications.

Research Areas

Students who focus on human factors in the industrial engineering program study:

• Ergonomics: workplace analysis, mental workload evaluation, biomechanics, modeling crash impacts, human reliability modeling, safety planning, and work physiology
• Human-centered design: ergonomic product design and analysis, design cognition, human and social dynamics in design, and problem-solving enabling methods
• Human-Computer interaction: human-computer interface and information visualization
• Human-Machine systems: human-in-the-loop simulation, behavioral decision-making modeling, human performance modeling, machine learning, and eye-tracking systems

Career options are vast for students who follow the human factors path, from positions in government research centers to software engineering companies to insurance companies and more.

Some examples of positions held by those who focus on human factors and ergonomics include: business intelligence team leader, cognitive engineer, cognitive systems engineer, design manager, ergonomics assessment specialist, ergonomics expert, human-centered designer, human factors design engineer, systems engineer, usability expert, user experience engineer, and user researcher.

Faculty members who specialize in human factors are:

• Christopher Dancy
• Scarlett Miller
• Ling Rothrock

Students who focus on manufacturing in the industrial engineering program learn through classroom instruction and hands-on projects in:

• Digital design and manufacturing: Areas of expertise include computer-aided design and manufacturing (CAD/CAM), integrated product development, product family and platform design, design analytics, geometric dimensioning and tolerancing, assembly planning, flexible and automated fixturing, automated process planning, non-destructive testing and evaluation, and virtual reality environments for design and manufacturing.
• Manufacturing processes: Advanced and traditional manufacturing processes including 3D printing and additive manufacturing, computer numerical controlled (CNC) machining, forming and joining processes, lightweight material casting, micro-machining and micro-forming, nanotechnology, intelligent materials processing, robotics, automation, and machine tool and discrete part metrology.
• Manufacturing system informatics and control: Focus areas include advanced sensing, process modeling, machine control, computer-integrated manufacturing, scheduling production and maintenance, distributed control systems, inventory and transportation management in supply chains, energy-aware operations of manufacturing enterprises, facility layout, and workplace design.

Students who focus on manufacturing in the industrial engineering program at Penn State have rewarding careers in academia, government, and industry, in areas such as manufacturing operations, production engineering, process control, quality engineering, Lean Six Sigma, product design and specification, cost analysis, and supply chain management, as well as in research and development jobs.

Faculty members who specialize in manufacturing are:

• Saurabh Basu
• Edward De Meter
• Sanjay Joshi
• Ilya Kovalen ko
• Soundar Kumara
• Jingjing Li
• Vittal Prabhu
• Timothy Simpson
• Robert Voigt

Students who focus on operations research in the industrial engineering program study:

• Applied probability and stochastic systems: queuing systems, stochastic networks, control of telecommunications and information systems, call center modeling, and large-scale service systems
• Financial engineering: auctions, real options, dynamic pricing of transportation services, mobile electronic commerce, and applied economics
• Game theory: dynamic games, network equilibrium, variational inequalities, and equilibrium programming
• Optimization: large-scale optimization, convex optimization, location theory, network optimization, integer programming, optimization of traffic networks, multiple criteria decision making, robust optimization, and compressed sensing
• Statistics and machine learning: statistical learning theory, spatial statistics, time series models, response surface methods, analysis and design of experiments, and large-scale statistical inference
• Quality engineering: total quality systems, process improvement strategies, design for quality, statistical modeling of tolerances, Taguchi loss function, and continuous quality improvement
• Simulation: production modeling, operational scheduling, plant design and layout, process flow analysis, and robust optimization

Graduates who have concentrated on operations research have obtained job titles such as: analytics and operations research engineer, applied research manager, lead performance engineer, operations research analyst, operations research scientist, professor in academia, process improvement engineer, research operations manager, senior director of global business intelligence and analytics, senior operations engineer, and statistician in industry.

Faculty members who specialize in operations research are:

• Serhat Aybat
• Enrique del Castillo
• Prakash Chakrabor ty
• Qiushi Chen
• Terry Friesz
• Catherine Harmonosky
• Uday Shanbhag
• Anirudh Subramanyam
• Jose Ventura

Note: The department houses the Operations Research (OR) Intercollege Graduate Degree Program . This allows students to receive dual master’s or doctoral degrees in their degree program while earning a secondary degree in OR.

Students who focus on production, supply chain, and service enterprise engineering in the industrial engineering program study:

• Health systems engineering: health information technology, patient flow modeling, capacity management, staff scheduling, quality improvement, data visualization, health informatics, and cost-effective modeling
• Production and distribution systems: material handling systems, material requirements planning, facility planning, capacity expansion, adaptive forecasting, multistage sequencing, and lean manufacturing
• Service engineering: retail engineering, workforce modeling, data mining, demand management, pricing, employee training, employee retention, and resource allocation
• Supply chain engineering and logistics – network design, enterprise integration, supply chain coordination and collaboration, contracting mechanisms, congestion modeling, and transportation modeling

Students who have focused their studies in production, supply chain, and service enterprise engineering have gone on to careers as: analytics managers, associate managers of global statistics, commodity managers, directors of quality assurance, fixture design managers, global/strategic sourcing managers, industrial and operations engineers, new product introduction engineers, process engineers, process improvement managers, quality engineer senior managers of e-commerce, senior material scientists, service business development managers, Six Sigma analysts, and supply chain analysts.

Faculty members who specialize in production, supply chain, and service engineering are:

• Prakash Chakr aborty

Research Applications

• Additive Manufacturing
• Big Data Analytics
• Energy Systems
• Health Care Engineering
• Service Enterprise Engineering
• Smart Manufacturing

Home of the first established industrial engineering program in the world, the Harold and Inge Marcus Department of Industrial and Manufacturing Engineering (IME) at Penn State has made a name for itself in the engineering industry through its storied tradition of unparalleled excellence and innovation in research, education, and outreach.

We are Innovators. We are Makers. We are Excellence in Engineering. We are Penn State IME.

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Graduates of IEOR are problem solvers. They use application of engineering methodology to non-traditional engineering problems. This skill set allows graduates to work in a wide variety of sectors, including financial services, consulting, manufacturing, technology, government, non-for-profit, and academia. For resources on finance, consulting, technology, startups and other fields of interest to IEOR majors, visit the CCE Industry Exploration pages . See what Columbia students have gone on to do with their degree with CCE’s  What Can You Do With A Degree in Industrial Engineering and Operations Research  tipsheet.

An operations manager ensures smooth operation of various processes that contribute to the production of goods and services of an organization. While the manager may not be specialist in any field, expectation is to perform well in various different roles. Some roles and responsibilities of an operations manager include:

• Delivery management : ensure delivery is on-time and goods and services meet quality criteria, obtain feedback from clients and communicate it to concerned departments
• Logistics management : coordinate with quality assurance personnel to ensure that goods produced meet acceptable standards and positive feedback from clients
• Budget management : coordinate with finance department to obtain necessary approval for budget, and ensure that quality equipment are maintained
• Third-party relation management : ensure the adherence of standard procedures in hiring of outside services, and the proper execution of the agreed terms
• Inventory management : ensure that the raw materials received are properly stored and conserved
• Operational strategizing : decide how to make optimum use of resources for organization, and determine the types of equipment needed to fulfill organizational quality policy

Other Professions in Operations Management

• IT Operations Manager : oversee teams of programmers, software engineers, and other professionals in dealing with data computing
• Financial Operations Manager : oversee company’s entire finances, analyze reports to ensure company is working within budget, perform financial forecasts
• Operations Manager Research Analyst : decide how to allocate a company’s resources, such as time, people, space, money and raw materials, to ensure profits
• System Center Operations Manager : ensure that a company’s computer network is running
• Quality Assurance Operations Manager : lead tests and inspection of products to ensure that products are free from defects
• Industrial Production Operations Manager : perform employee scheduling, hiring and terminations, quality control, maintenance and coordinating the entire unit’s activity
• Marketing Operations Manager : analyze demand and monitor consumer trends in order to find the most effective marketing strategy, forecast revenues and establish prices
• Purchasing Operations Manager : acquire all goods and services that are needed for a company’s operation
• Clinical Operations Manager : oversee laboratory procedures, ensuring that lab follows all procedures in regards to safety
• Real Estate Operations Manager : oversee the purchases and sales of properties for a business or private investors
• Supply Chain Management : coordinate of efforts of a network of vendors that provides specific materials and components for a company’s products.

For more details on the work of Industrial Engineers, visit the  IEOR department website , as well as the  Sloan Cornerstone Career Center ,  TryEngineering , and the  Occupational Outlook Handbook .

Industrial Engineering/Operations Research Job Search

While some large organizations may recruit in the Fall semester, many others will seek full-time hires on an “as needed” basis. The key is to start your search early so that you do not miss opportunities. Use resources like the professional associations listed below to apply to positions and seek out networking opportunities, attend CCE’s Engineering Consortium Career Fair and Engineering Industry Showcase, and pay attention to your departments’ emails. Many industrial engineers go on to earn a graduate degree. These programs tend to involve more research and independent study. Graduate degrees are usually required for teaching positions. Entry-level industrial engineers find jobs in various departments, such as computer operations, warehousing, and quality control. As engineers gain on-the-job experience and familiarity with departments, they may decide on a specialty. Industrial engineering jobs are often considered stepping-stones to management positions, even in other fields. Engineers with many years’ experience frequently are promoted to higher-level jobs with greater responsibilities.

Columbia Resources

• Career Fairs and Networking Events : Attend our career fairs and special events throughout the year including the Engineering Career Fair and Startup Career Fair.
• Engineering Industry Showcase : Held in the Spring semester, offers a panel session and networking opportunities with representatives from a variety of engineering disciplines.
• List of  Leadership Development and Rotational Programs
• Vault  (formerly Firsthand) guides: Offers profiles of industries, companies, and careers including  Engineering ,  Industrial Engineers , and Operations and Logistics
• IEOR Department Website
• Student Research Involvement Program
• Information on the  FE Exam  (Students should find out from their academic advisor whether their desired career path requires EIT/PE certification)
• Fellowships for  CC/SEAS  and  GS

External Resources

Professional associations.

• Institute of Industrial Engineers (IIE)
• International Council on Systems Engineering (INCOSE)

Internship/Job Boards   

• EngineerJobs.com : This component of the Engineer Jobs site is catered specifically to jobs in the industrial engineering industry
• Pathways to Science : To find programs such as undergraduate summer research opportunities, graduate fellowships, postdoctoral positions, as well as resources and materials pertaining to recruitment, retention, and mentoring
• National Science Foundation REU Sites : The Research Experiences for Undergraduates (REU) program supports active research participation by undergraduate students in any of the areas of research funded by the National Science Foundation
• American Academy for Advancement of Science : A resource list of AAAS career development programs
• ACECNY : A proactive coalition of more than 270 firms representing every discipline of engineering related to the built environment — civil, structural, mechanical, electrical, geotechnical — and affiliated companies.
• Research Gate : A network dedicated to science and research. Connect, collaborate and discover scientific publications, jobs and conferences
• Engineering Central : Lists engineering positions and resumes across all engineering disciplines

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Home > Engineering > MIE > Industrial Engineering & Operations Research Masters Theses Collection

Industrial Engineering & Operations Research Masters Theses Collection

Theses from 2023 2023.

Mining High Impact Combinations of Conditions from the Medical Expenditure Panel Survey , Arjun Mohan, Industrial Engineering & Operations Research

Theses from 2022 2022

Systematic Review of Driver Distraction in the Context of Advanced Driver Assistance Systems (ADAS) & Automated Driving Systems (ADS) , Apoorva Pramod Hungund, Industrial Engineering & Operations Research

Theses from 2021 2021

Comparing and Improving the Design of Physical Activity Data Visualizations , Peter M. Frackleton, Industrial Engineering & Operations Research

Robustness of Supply Chain Synchronization Strategies , Andrew Frere, Industrial Engineering & Operations Research

Theses from 2020 2020

Optimal Mammography Schedule Estimates Under Varying Disease Burden, Infrastructure Availability, and Other Cause Mortality: A Comparative Analyses of Six Low- and Middle- Income Countries , Shifali Shifali, Industrial Engineering & Operations Research

Theses from 2019 2019

ADVANCED VIRTUAL REALITY HEADSET BASED TRAINING TO IMPROVE YOUNG DRIVERS’ LATENT HAZARD ANTICIPATION ABILITY , Ravi Agrawal, Industrial Engineering & Operations Research

THE EVACUATION PROBLEM IN MULTI-STORY BUILDINGS , Quang Hong Cung, Industrial Engineering & Operations Research

MARKOV DECISION PROCESS APPROACH TO STRATEGIZE NATIONAL BREAST CANCER SCREENING POLICY IN DATA-LIMITED SETTINGS , Vijeta Deshpande, Industrial Engineering & Operations Research

A Computational Simulation Model for Predicting Infectious Disease Spread using the Evolving Contact Network Algorithm , Buyannemekh Munkhbat, Industrial Engineering & Operations Research

Effects of Task Load on Situational Awareness During Rear-End Crash Scenarios - A Simulator Study , Rajiv Nair, Industrial Engineering & Operations Research

Theses from 2018 2018

Does the Elicitation Mode Matter? Comparing Different Methods for Eliciting Expert Judgement , Claire Cruickshank, Industrial Engineering & Operations Research

The Application of Usability Engineering Methods to Evaluate and Improve a Clinical Decision Support System , Kristine DeSotto, Industrial Engineering & Operations Research

Evaluation and Validation of Distraction Detection Algorithms on Multiple Data Sources , Shashank Mehrotra, Industrial Engineering & Operations Research

Impact of Perceptual Speed Calming Curve Countermeasures On Drivers’ Anticipation & Mitigation Ability – A Driving Simulator Study , Krishna Valluru, Industrial Engineering & Operations Research

Theses from 2017 2017

Explorations into Machine Learning Techniques for Precipitation Nowcasting , Aditya Nagarajan, Industrial Engineering & Operations Research

Theses from 2016 2016

Simulation of 48-Hour Queue Dynamics for A Semi-Private Hospital Ward Considering Blocked Beds , Wei Chen, Industrial Engineering & Operations Research

Strategies for Reducing Supplier Risk: Inputs into the Supply Chain , Christopher A. Greene, Industrial Engineering & Operations Research

Aircraft Demand Forecasting , Kayla M. Monahan, Industrial Engineering & Operations Research

Theses from 2015 2015

Evaluation of a Training Program (STRAP) Designed to Decrease Young Drivers Secondary Task Engagement in High Risk Scenarios , Akhilesh Krishnan, Industrial Engineering & Operations Research

Theses from 2014 2014

Delivery Performance Prediction Tool for Complex Assembly Systems , Faried D. Beladi, Industrial Engineering & Operations Research

Investigating Teenage Drivers' Driving Behavior before and after LAG (Less Aggressive Goals) Training Program , Jingyi Zhang, Industrial Engineering & Operations Research

Theses from 2013 2013

Endogenous Technological Change In The Dice Integrated Assessment Model , Robert W. Barron, Industrial Engineering & Operations Research

Factors Which Influence Key Entry Speed On Hard and Soft Keyboards: Experience, Eye Behaviors and Finger Movements , Seckin Celik, Industrial Engineering & Operations Research

Comparing the Present U.S. Electricity Grid to a Smart Grid System , Charthamkudath Jubith Sadanandan, Industrial Engineering & Operations Research

Using Computer Simulation to Study Hospital Admission and Discharge Processes , Edwin S. Kim, Industrial Engineering & Operations Research

An Evaluation of Methods to Assess Whether Health Information Technology-Based Tools Improve Weight Loss Measures in Bariatric Surgery Patients , Jocelyn R. Morgan, Industrial Engineering & Operations Research

Effects of Different Methods of Aggregation of Probabilities on the R&d Investment Portfolio for Optimal Emissions Abatement: An Empirical Evaluation , Olaitan P. Olaleye, Industrial Engineering & Operations Research

Water Plans and Climate Change Plans in the Northeast and the Southwest , An Pham, Industrial Engineering & Operations Research

Theses from 2012 2012

The Process by which Physicians Extract Information from Electronic Progress Notes During Handoffs , Brian D. Amster, Industrial Engineering & Operations Research

Dynamic Capacity Allocation in Primary Care with Physician Flexibility , Sebastian S. Biehl, Industrial Engineering & Operations Research

Impacts of Solar Grid Integration Issues on the Optimal Energy R&d Portfolio for Climate Change , Noubara Djimadoumbaye, Industrial Engineering & Operations Research

Using Discrete Event Simulation to Evaluate the Impact of Adding a Fast Track Section to a Crowded Emergency Department , Yan Jin, Industrial Engineering & Operations Research

The Economic Impacts of Technical Change in Carbon Capture , Peter G. Rasmussen, Industrial Engineering & Operations Research

Optimizing the Safety Stock Inventory Cost Under Target Service Level Constraints , Chetan T. Shivsharan, Industrial Engineering & Operations Research

Development of a Cost Minimizing Strategy to Mitigate Bird Mortalities in a Wind Farm , Karamvir Singh, Industrial Engineering & Operations Research

Theses from 2011 2011

The Effect of External Distractions on Novice and Experienced Drivers' Anticipation of Hazards and Vehicle Control , Gautam Divekar, Industrial Engineering & Operations Research

Methods to Study Nurses’ Visual Scanning Patterns during the Medication Administration Process , Ze He, Industrial Engineering & Operations Research

Reverse Logistics Network Design for Electric Vehicle Batteries , Tilman Schnellenpfeil, Industrial Engineering & Operations Research

Theses from 2010 2010

Electronic Falls Reporting System Implementation: Evaluating Data Collection Methods and Studying User Acceptance , Yi You Mei, Industrial Engineering & Operations Research

Electric Power Market Modeling with Multi-Agent Reinforcement Learning , Nathanael K. Miksis, Industrial Engineering & Operations Research

A Stochastic R&d Portfolio Model under Climate Uncertainty , Yiming Peng, Industrial Engineering & Operations Research

Optimal Energy R&d Portfolio Decision Making under Climate Change Uncertainty , Georg Schorpp, Industrial Engineering & Operations Research

Evaluation of an Eye Tracking Device to Increase Error Recovery by Nursing Students Using Human Patient Simulation , Yan Shen, Industrial Engineering & Operations Research

The Impact of Flexibility And Capacity Allocation On The Performance of Primary Care Practices , Liang Wang, Industrial Engineering & Operations Research

Theses from 2009 2009

A Discrete Event Simulation Approach to Resource Management, Process Changes And Task Prioritization in Emergency Departments , Ekkehard C. Beck, Industrial Engineering & Operations Research

Development of a Decision Tool for Green Energy Investment in the Pioneer Valley , Benjamin R. Ewing, Industrial Engineering & Operations Research

Physician Flexibility in Primary Care Practices , Jan T. Hippchen, Industrial Engineering & Operations Research

Optimal Acquisition and Sorting Policies for Remanufacturing over single and Multiple Periods , Yihao Lu, Industrial Engineering & Operations Research

Theses from 2008 2008

Evaluation of a Simulator Based, Novice Driver Risk Awareness Training Program , Frank Diete, Industrial Engineering & Operations Research

The Effect of Price Postponement on the Coordination of a Two Stage Supply Chain Facing Consumer Returns , Thomas Lenk, Industrial Engineering & Operations Research

Impacts Of Asymmetric Decision Policies And Consumer Behavior On Supply Chain Coordination Under Consumer Returns , Harald Schmid, Industrial Engineering & Operations Research

Theses from 2007 2007

Agent Based Modeling of Electronic Markets To Analyze the Sustainability of Mutual Cooperation , Ravindra R. Lote, Industrial Engineering & Operations Research

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Independent Study Topics in Mechanical and Industrial Engineering

Participation in research can be a rewarding component of an undergraduate engineering program. Motivated students can earn credit and satisfy some elective degree requirements by conducting independent study or thesis research with a supervising faculty member. Alternatively, students can be paid to conduct research; for example, by completing a summer Research Experience for Undergraduates (REU) program at UMass or at another university.

Most undergraduate research projects are “arranged” by the student who meets with faculty to discuss research interests and needs. Students often consult  faculty web pages  for overviews of faculty research interests and contact information for prospective advisors. Most faculty members welcome undergraduate researchers to their labs, and many can create undergraduate research projects reflecting student interests and capabilities that are related to their own research. Other projects may be more clearly defined in advance by faculty members, derive from other projects, or reflect a new idea that a student wishes to explore. Descriptions of some of the more well-defined research projects follow. Students interested in any of these projects or in other research topics are encouraged to contact the associated faculty members.

Professor Erin Baker :  

My research is on energy technology policy, especially related to  energy equity and the transition to a low carbon energy system. The methods are mathematical and computational decision modeling. Examples of current honors topics include modeling the impact of heat pumps on electricity demand in New England and evaluating energy storage options, including cooperatively owned and operated batteries and hot water storage.

Professor Wen Chen :  

Our  Multiscale Materials and Manufacturing Laboratory  is very interested in hosting students for research intern, independent study, or senior project throughout the year. Our research group is focused on advanced manufacturing of structural and functional materials using various 3D printing technologies. Structural metal alloys that we study include Al alloys, steels, high entropy alloys, metallic glasses, and 3D architected materials (also called mechanical metamaterials). We also collaborate with many other universities (UPenn, Brown, Stanford, Georgia Tech), national labs (Oak Ridge National Lab, Lawrence Livermore National Lab, Argonne National Lab), and industry partners to develop next-generation eco-friendly batteries. Our lab houses a wide range of 3D printing facilities including direct ink writing, laser powder bed fusion, laser engineered net shaping, and plasma wire arc additive manufacturing system. We have a multidisciplinary team working on alloy development, mechanical behavior of 3D-printed materials, powder metallurgy, and electrochemistry.     If you are interested in applying for research opportunities in our lab, please send a CV to wenchen [at] umass [dot] edu (Dr. Wen Chen) .  

Professor Steve de Bruyn Kops :  

I study fluid turbulence at a very fundamental level. Fundamental science, not engineering. I can work with students who have some appreciation for how to move massive amounts of data through a computer (files larger than the hard drive on a laptop). Knowledge of python and C++ is good. Excel and Matlab are not adequate. In particular, I am looking for a student with these computer skills and an interest in learning something about artificial intelligence, data mining, and/or big data.

Professor Xian Du : 

I am very interested in the supervision of senior students. Following are my research areas (please also refer to my Google Scholar page here ): Roll to Roll Flexible Electronics Printing Intelligent Vision Medical Device Realization Specific projects regarding which I would like to meet students to discuss include: The design, realization, control, and scale up of Roll to Roll Print Machines. You will work with me and my PhD students who have rich industrial experience, and my industrial collaborators in the project. You will learn both hand-on skills in design and programming, many interesting research directions in the manufacturing of flexible electronics. This project will be good for students who are interested in precision machine design, control, and manufacturing. Machine vision, image processing, machine learning, and data mining for nanomanufacturing, or medical devices. The data can be from MRI, high-speed/high-resolution optical and NIR camera, or microscope. You will learn the how to apply AI to the above areas. You also will learn how to solve fundamental problems in setup, calibration, and using of these imaging devices. You have chance to work with both my industrial and hospital collaborators. This project will be good for students who are interested in AI applications and discovery of novel AI computations.

Professor Chaitra Gopalappa :  

My research area and previous work can be found here . Students interested in doing a CHC thesis or independent study should contact me at  chaitrag [at] umass [dot] edu (chaitrag[at]umass[dot]edu)  to set up an appointment to discuss specific projects of interest. Students can expect to use one or more of stochastic processes, optimization, simulation, computational modeling, and data analytics. Students can expect to work in the "broad" area of disease prevention and control, though the methodologies can be transferable to other areas.

Professor Meghan Huber : 

The mission of the Human Robot Systems Lab is to advance how humans and robots learn to guide the physical interactive behavior of one another. To achieve this, our research aims to: (1) develop new methods of describing human motor behavior that are compatible for robot control, (2) understand and improve how humans learn models of robot behavior, and (3) develop robot controllers that are compatible for human-robot physical collaboration. This highly interdisciplinary research lies at the intersection of robotics, dynamics, controls, human neuroscience, and biomechanics. To apply, please follow the instructions here .

Professor Juan Jiménez :

The research goal of the Jiménez laboratory at the University of Massachusetts Amherst is to elucidate the fluid flow characteristics and fluid flow-dependent biomolecular pathways relevant to diseases and processes in the body, by integrating fluid dynamic engineering into cellular and molecular mechanisms important in medicine. Our research focuses on experimental cardiovascular biomedicine; specifically, addressing the interaction of flow in the blood vasculature and lymphatic system with the endothelium. Furthermore, we also work in the area of biomedical implantable devices like stents. Active areas of research are: Atherosclerosis & Stents: Elucidating the role of fluid flow on endothelial cell migration by investigating cell motility, reactive oxygen species, and gene expression Cerebral Aneurysms & Stroke: Recreating the fluid flow environment present in the cerebral vasculature to identify pro-inflammatory endothelial cell gene expression Vascular Biology: In-vitro models of disease and endothelial cell phenotype

Professor Jim Lagrant :  

I typically advise 2–3 independent study projects each semester in industrial automation, engineering education, machine design and fabrication. Topics include selection and application of industrial control hardware, Programmable Logic Controller programming, Human Machine Interface design and programming, classroom aid and laboratory experiment design, and equipment redesign. Students interested in doing a CHC thesis or independent study should contact me at  jlagrant [at] umass [dot] edu (jlagrant[at]umass[dot]edu)  to set up an appointment to discuss specific projects of interest.

Professor Jae-Hwang Lee :  Nano-Engineering Laboratory

We are looking for a few research-oriented undergraduates interested in materials in mechanical extremes. Their material research topics could potentially relate to bulletproof materials or additive manufacturing. We prefer a research plan more extended than one semester.

Professor Tingyi “Leo” Liu :

My Inter²EngrLAB  welcomes any passionate undergraduate students who want to step out of their comfort zone to prepare themselves for the challenging future. We work on interdisciplinary topics and aim to advance fundamental science and develop enabling technologies in the fields such as Micro Electromechanical Systems (MEMS), nanotechnology, brain-machine interface, soft electronics and robotics, listing just a few. Example projects include neurosurgical robots, automated nanomanufacturing systems, multifunctional neural probes, super-repellent surfaces. Our projects offer students research experience on mechatronics, CNC machining, MEMS, control systems, hardware-software interface programming, lithography, app design, bioinspired design, human-factor product design, etc., with hardcore training in both hands-on and theory as well as interdisciplinary communication. We have opportunities for students to do research intern, senior design projects, independent studies, and honor thesis that may involve all phases of academic research, technology transfer and development, and industrial product development. I individually train students who are interested in working with me to maximize their potential and let them work with everyone in my lab to encourage diversity and inclusivity. Feel free to talk to me for more in-depth discussion on possible projects.

Professor Yahya Modarres-Sadeghi :  

I always have projects for undergraduate students: General Fluid-Structure Interactions (FSI) problems, mainly experimental, with specific problems being those in which the students conduct experiments in the water tunnel or wind tunnel for either fundamental FSI problems, fish propulsion, wind energy related projects, or our bat deterrent device. I also have projects on biomedical FSI.

Professor Jinglei Ping:  

The goal of Ping Lab  is to determine the fundamental principles governing applications of nanomaterials and nanomaterial-based device structures in biotechnology, healthcare, environmental monitoring, and so on. Fascinating phenomena emerge as materials or devices scale down, inducing "surprises" and offering promise for dramatic improvement in the material or device performances. However, not all "surprises" are favorable. Moreover, fabrication and investigation at micro or nano scales can be technically challenging. We tackle the challenges by combining techniques in bioelectronics, microfluidics, microscopy, microfabrication and more (sometimes we invent the techniques) to harness innovative physicochemical principles at micro or nano scales to create devices and systems for processing, detecting, and/or stimulating biosystems. We are an energetic lab focusing on interdisciplinary research. If you are interested in novel nanomaterials, understanding their bio-transducing properties, building nano-enabled biosensors, etc., reach out to us at  ping [at] engin [dot] umass [dot] edu (ping[at]engin[dot]umass[dot]edu) ! Students from underrepresented groups are particularly encouraged.

Professor Anuj K. Pradhan : 

The  Pradhan Research Group  operates as part of the  Human Performance Laboratory . Our group conducts research on driver behaviors in the context of driving safety, with a specific focus on advanced vehicle technologies including Connected and Automated Vehicles. Past and current students (undergraduate and graduate) have worked on research projects on: Human Factors of Automated Vehicles, Distracted Driving, Impact of Advanced Technologies on Driver Safety, user-centered design for automotive interfaces, and Driving Simulation Methodologies. These projects are undertaken using an advanced Driving Simulator, or are conducted on public roadways with advanced vehicles, or via analytical human factors methods. Students in the group will have opportunities to be involved in all phases of a research study, from conceptualization and design and preparation of experiments, to data collection, data analyses, and reporting of results. Students will also have opportunities to independently conduct research of their interest if that overlaps with the group’s interests. Our group students are encouraged to and regularly present their research at conferences at UMass or at domestic conferences and are supported financially to do so. Please visit the  group website  to learn more and to contact Professor Pradhan. 

Professor Shannon Roberts : 

The  Roberts Research group , a part of the  Human Performance Laboratory , is always interested in having undergraduate students join our research team. Broadly speaking, our work is focused on Human Factors in transportation safety. We look at how to improve driving behavior among young adults and teens. We also examine issues in driving automation systems, including how to design in-vehicle interfaces & training systems and differences in performance across demographic groups. Undergraduate students have the opportunity to use a variety of tools (e.g., driving simulators) and are typically involved in all stages of research, from ideation to research design to analysis to publishing.

Professor Jonathan Rothstein :  

I am always willing to supervise experimental fluid dynamics projects. The list of possible projects is long, and I usually have 10 or so that I sketch out for any student who is interested in working with me. I let them pick out the one that they like best.

Professor Krish Thiagarajan Sharman:  

I am interested in working with one or two honors students in the following topics: Modeling an offshore wind turbine using industry standard software. Explore new concepts and produce interesting simulation results. No computing skills needed, but interest in learning new skills is essential. Design, build and test an offshore wind turbine platform in our wave tank (Gunness Hall). Knowledge of SolidWorks is essential. Hands-on work in the workshop will be required.

Professor Yubing Sun :  

Potential projects for undergraduate honors research include: using microfluidic devices to study the mechanotransduction in epithelial cells, using engineered hydrogels and pluripotent stem cells to model early neural development, and imaging analysis using Matlab to track cell migration and proliferation.

Professor Frank Sup :  The Mechatronics and Robotics Research Laboratory

I am looking for students interested in the areas of: Robot design Biomechanics of human locomotion Collaborative human-robot systems Robot tele-operation

Professor Yanfei Xu : Xu Research Group at UMass Amherst

We are looking for like minded scientists and engineers with synergistic research interests to work together on  multifunctional polymers, integrated devices and systems, and advanced manufacturing. Applicants should send cover letter and curriculum vitae through email to  yanfeixu [at] umass [dot] edu (subject: Xu%20Research%20Group) (yanfeixu[at]umass[dot]edu) .

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Research & Innovation - School of Industrial Engineering - Purdue University

Purdue engineers have an interest in changing the world, making an impact in their communities, and doing meaningful work. Strong leadership characteristics, ingenuity, adaptability, critical thinking, problem solving skills, and technical proficiency are among the main competencies that our students gain. Purdue engineering is dedicated to helping students attain the skills and attributes needed to succeed in this rapidly-changing global economy.

Human Factors Faculty Members

Operations Research Faculty Members

Production Systems Faculty Members

Undergraduate Research

Labs & Centers

Manufacturing Faculty Members

Call for Paper - Upcoming Issues Upcoming Conferences 2024 -->

List of topics.

SSRG International Journal of Industrial Engineering (SSRG-IJIE) is a journal that publishes articles which contribute new novel experimentation and theoretical work in in all areas of Industrial Engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical Industrial Engineering.

• Engineering economic analysis
• Computer methods for engineering
• Engineering experimental design
• CIMS, robotics and automation
• Quality engineering, environment risk analysis
• Systems reliability engineering, maintenance analysis
• Human factors/ergonomics in design
• Simulation modelling/analysis
• System design and control systems, concurrent engineering
• Production systems analysis/design
• Facilities layout/design
• Financial/investment engineering
• Information systems, ICT, AI/expert systems design
• Project management, decision support systems
• Technology management/transfer
• Business and strategy, decision analysis
• Engineering economy, cost estimation
• Environmental issues
• Facility location, layout, design, materials handling
• Human factors, ergonomics, safety
• Education, case studies
• ICT and information systems
• Innovation, knowledge management, organisational learning
• Inventory, logistics, transportation, supply chain management
• Manufacturing, control, automation
• Product/process design and management
• Forecasting, production planning/control
• Project/operations management, scheduling
• Service systems/management, performance analysis, modelling/simulation
• TQM/quality engineering, reliability/maintenance engineering

Any other topics relevant to latest trends in Industrial Engineering

• Department of Industrial and Systems Engineering >
• Research >
• Research Areas >

Security and Defense

Our research improves the efficiency and effectiveness of security and defense systems. 

Research in this area includes the development of solutions to optimize the use of sensor networks, including unmanned vehicles using operations research and data fusion methods, improved homeland security through the use of data fusion and game theory, and enhanced trust and decision-making performance in human-automation interactions with security and defense technology.

Sponsors include the National Science Foundation, US Department of Homeland Security, US Navy, USAF Research Laboratory, Defense Threat Reduction Agency Office of Naval Research, Army Research Laboratory Defense Intelligence Agency, US Space Force, Alion (AFRL-Rome), Sierra Nevada Corporation, Overwatch Systems, Raytheon C3 Systems and General Dynamics – AIS.

Affiliated Faculty

• Rajan Batta , PhD
• Ann Bisantz , PhD
• Robert Dell , PhD
• Chase Murray , PhD
• Prashant Sankaran , PhD
• Moises Sudit , PhD
• Jose Walteros , PhD
• Jun Zhuang , PhD

Selected Research Topics

Sensor networks and unmanned vehicles.

Sensors in a data fusion environment over hostile territory are geographically dispersed and change location with time. To collect and process data from these sensors, a flexible network of fusion beds (i.e., clusterheads) is required. The research focuses on modeling and solving problems that arise from multiple sensors working in a particular situation. Most of these problems occur in dynamic environments, where special methodologies are required.

Data Fusion and Homeland Security

Research projects focus on developing methods of enhancing national security and improving the accuracy of intelligence gathering. Information fusion works by combining evidence and intelligence gathered from a wide variety of sources, which when considered separately often yield conflicting and ambiguous results. The system combines and organizes the information from such sources as remote satellites, sensors, and individual personnel, and then incorporates it in a seamless flow to a central command center, where decisions can be more effectively rendered. 

Game Theory and Homeland Security Resource Allocation

Hundreds of billions of U.S. dollars have been allocated to homeland security since 9/11/2001. How to optimally allocate these resources remains a challenging issue, especially considering the fact that adversaries are intelligent and adaptive. In this research, operations research and game theory are integrated to study the optimal defensive resource allocation. The tradeoffs between preparedness and relief, between efficiency and equity, and between private and public investment are also studied.

Information Visualization Research

A number of research projects have addressed the visualization of information relevant for command-and-control operations. Information may come from physical sensors with inherent uncertainty, different values may be provided by different sensors or sources, or future events or states may be difficult to predict. The relationships between information presentation methods including the use of graphical variables (color components, blurriness, and transparency) and multi-modal methods such sound and vibration, and human decision-making performance are studied.

Human Trust and Performance

Research in this area includes studies of trust in automated decision aids, particularly under circumstances where information provided by the aids has been degraded or corrupted. A focus of this work has been decision making in aided, adversarial situations, when decision aids include fused or processed information. 

Airport Security

The research has integrated human factors, operations research and game theory to help authorities better prepare for, mitigate, and manage both natural and man-made hazards in systems such airport security systems. The emphasis thus far has been on the impact of humans and the available technologies on security system reliability and efficiency.

150+ Best Engineering Research Topics for Students To Consider

Table of Contents

Engineering is a wide field of study that is divided into various branches such as Civil, Electrical, Mechanical, Electronics, Chemical, etc. Basically, each branch has thousands of engineering research topics to focus on. Hence, when you are asked to prepare an engineering research paper or dissertation for your final year assignments, you might experience difficulties with identifying a perfect topic. But hereafter, you need not worry about topic selection because to make the topic selection process easier for you, here we have suggested some tips for choosing a good engineering research topic. Additionally, we have also shared a list of the best 150+ engineering research paper topics on various specializations. Continue reading this blog to get exclusive ideas for engineering research paper writing.

Engineering Research Paper Topic Selection Tips

When it comes to research in the field of engineering, identifying the best engineering research topic is the first step. So, during that process, in order to identify the right topic, consider the following tips.

• Choose a topic from the research area matching your interest.
• Give preference to a topic that has a large scope to conduct research activities.
• Pick a topic that has several reference materials and evidence supporting your analysis.
• Avoid choosing an already or frequently discussed topic. If the topic is popular, discuss it from a different perspective.
• Never choose a larger topic that is tough to complete before the deadline.
• Finalize the topic only if it satisfies your academic requirements.

List of the Best Engineering Research Topics

Are you searching for the top engineering project ideas? Would you have to complete your academic paper on the best engineering research topic? If yes, then take a look below. Here, we have suggested a few interesting engineering topics in various disciplines that you can consider for your research or dissertation.

Mechanical Engineering Research Topics

• How does the study of robotics benefit from a mechanical engineering background?
• How can a new composite substitute reduce costs in large heat exchangers?
• Which will become the predominant energy technology this century?
• Why structural analysis is considered the foundation of mechanical engineering?
• Why is cast iron used in the engines of large ships?
• What is the finite element approach and why is it essential?
• Why is the flow of fluids important in mechanical engineering?
• What impact does mechanical engineering have in the medical field?
• How do sports incorporate mechanical engineering theories?
• What is the process of thermal heat transfer in machines?
• How can solar panels reduce energy costs in developing countries?
• In what ways is mechanical engineering at the forefront of the field?
• How do various elements interact differently with energy?
• How can companies improve manufacturing through new mechanical theories?

Additional Research Paper Topics on Mechanical Engineering

• Power generation: Extremely low emission technology.
•   Rail and wheel wear during the presence of third-body materials.
•  Studying the impact of athletic shoe properties on running performance and injuries
• Evaluating teeth decay using patient-specific tools
•   Nanotechnology.
• Describe the newly developed methods and applications in Vibration Systems
• Perspective or general Commentaries on the methods and protocols relevant to the research relating to Vibration Systems
• Software-related technology for Visibility of end-to-end operations for employee and management efficiencies
• What should be the best strategies to apply in the planning for consumer demand and responsiveness using data analytics
• Analysis of the monitoring of manufacturing processes using IOT/AI
• Critical analysis of the advancing digital manufacturing with artificial intelligence (AI) and machine learning (ML) Data Analytics
• Pyrolysis and Oxidation for Production and Consumption of Strongly Oxygenated Hydrocarbons as Chemical Energy Carriers: Explain
• Explore the most effective strategies for fatigue-fracture and failure prevention of automotive engines and the importance of such prevention
• Explore the turbomachinery performance and stability enhancement by means of end-wall flow modification
• Production optimization, engine performance, and tribological characteristics of biofuels and their blends in internal combustion engines as alternative fuels: Explain

Civil Engineering Research Topics

• The use of sustainable materials for construction: design and delivery methods.
• State-of-the-art practice for recycling in the construction industry.
• In-depth research on the wastewater treatment process
• Building Information Modelling in the construction industry
• Research to study the impact of sustainability concepts on organizational growth and development.
• The use of warm-mix asphalt in road construction
• Development of sustainable homes making use of renewable energy sources.
• The role of environmental assessment tools in sustainable construction
• Research to study the properties of concrete to achieve sustainability.
• A high-level review of the barriers and drivers for sustainable buildings in developing countries
• Sustainable technologies for the building construction industry
• Research regarding micromechanics of granular materials.
• Research to set up remote sensing applications to assist in the development of sustainable construction techniques.
• Key factors and risk factors associated with the construction of high-rise buildings.
• Use of a single-phase bridge rectifier
• Hydraulic Engineering: A Brief Overview
• Application of GIS techniques for planetary and space exploration
•   Reengineering the manufacturing systems for the future.
• Production Planning and Control.
•   Project Management.
•   Quality Control and Management.
•   Reliability and Maintenance Engineering.

Environmental Engineering Research Paper Topics

• Design and development of a system for measuring the carbon index of energy-intensive companies.
• Improving processes to reduce kWh usage.
• How can water conductivity probes help determine water quality and how can water be reused?
• A study of compressor operations on a forging site and mapping operations to identify and remove energy waste.
• A project to set up ways to measure natural gas flow ultrasonically and identify waste areas.
• Developing a compact device to measure energy use for a household.
• What are carbon credits and how can organizations generate them?
• Production of biogas is from organic coral waste.
• Analyzing the impact of the aviation industry on the environment and the potential ways to reduce it.
• How can voltage reduction devices help organizations achieve efficiency in electricity usage?
• What technologies exist to minimize the waste caused by offshore drilling?
• Identify the ways by which efficient control systems using information systems can be introduced to study the energy usage in a machining factory.
• The process mapping techniques to identify bottlenecks for the supply chain industry.
• Process improvement techniques to identify and remove waste in the automotive industry.
• In what ways do green buildings improve the quality of life?
• Discussion on the need to develop green cities to ensure environmental sustainability
• Process of carbon dioxide sequestration, separation, and utilization
• Development of facilities for wastewater treatment

Read more topics: Outstanding Environmental Science Topics for You to Consider

Electrical Engineering Research Topics

• Research to study transformer losses and reduce energy loss.
• How does an ultra-low-power integrated circuit work?
• Setting up a control system to monitor the process usage of compressors.
• Integration of smart metering pulsed outputs with wireless area networks and access to real-time data.
• What are the problems of using semiconductor topology?
• Developing effective strategies and methodical systems for paying as-you-go charging for electric vehicles.
• A detailed review and investigation into the key issues and challenges facing rechargeable lithium batteries.
• Trends and challenges in electric vehicles technologies
• Research to investigate, develop and introduce schemes to ensure efficient energy consumption by electrical machines.
• What is meant by regenerative braking?
• Smart charging of electric vehicles on the motorway
• Research to study metering techniques to control and improve efficiency.
• Develop a scheme to normalize compressor output to kWh.
• Research to introduce smart metering concepts to ensure efficient use of electricity.
• What is the most accurate method of forecasting electric loads?
• Fundamentals of Nanoelectronics
• Use of DC-to-DC converter in DC (Direct Current) power grid
• Development of Microgrid Integration

Electronics and Communications Engineering Research Topics

• Developing the embedded communication system for the national grid to optimize energy usage.
• Improvement of inter-symbol interference in optical communications.
• Defining the boundaries of electrical signals for current electronics systems.
• The limitation of fiber optic communication systems and the possibility of improving their efficiency.
• Gaussian pulse analysis and the improvement of this pulse to reduce errors.
• A study of the various forms of errors and the development of an equalization technique to reduce the error rates in data.
• Realizing the potential of RFID in the improvement of the supply chain.
• Design of high-speed communication circuits that effectively cut down signal noise.
• Radiation in integrated circuits and electronic devices.
• Spectral sensing research for water monitoring applications and frontier science and technology for chemical, biological, and radiological defense.

Computer and Software Engineering Research Topics

• How do businesses benefit from the use of data mining technologies?
• What are the risks of implementing radio-controlled home locks?
• To what extent should humans interact with computer technologies?
• Are financial trading systems operating over the web putting clients at risk?
• What challenges do organizations face with supply chain traceability?
• Do chatbot technologies negatively impact customer service?
• What does the future of computer engineering look like?
• What are the major concepts of software engineering?
• Are fingerprint-based money machines safe to use?
• What are the biggest challenges of using different programming languages?
• The role of risk management in information technology systems of organizations.
• In what ways does MOOD enhancement help software reliability?
• Are fingerprint-based voting systems the way of the future?
• How can one use an AES algorithm for the encryption of images?
• How can biological techniques be applied to software fault detection?

Read more: Creative Capstone Project Ideas For Students

Network and Cybersecurity Engineering Research Topics

• Write about Cybersecurity and malware connection.
• How to detect mobile phone hacking.
• Discuss Network intrusion detection and remedies.
• How to improve network security using attack graph models.
• Explain Modern virus encryption technology.
• Investigate the importance of algorithm encryption.
• Discuss the role of a firewall in securing networks.
• Write about the global cybersecurity strategy.
• Discuss the Privacy and security issues in chatbots.
• Write about Cloud security engineering specifics

Industrial Engineering Research Paper Topics

• The application of lean or Six Sigma in hospitals and services-related industries.
• The use of operation research techniques to reduce cost or improve efficiency.
• Advanced manufacturing techniques like additive manufacturing.
• Innovation as a Complex Adaptive System.
• CAD-based optimization in any manufacturing environment.
• Gap analysis in any manufacturing firm.
• The impact of 3D printing in the manufacturing sector.
• Simulating a real-life manufacturing environment into simulating software
• The rise of design and its use in the developing world.
• Building a network-based methodology to model supply chain systems.
• Risk optimization With P-order comic constraint
• Technology and its impact on mass customization
• How project management becomes more complex with disparate teams and outsourced functions?
• Scheduling problem for health care patients.

Biomedical Engineering Research Ideas

• How does the use of medical imaging help patients with higher risks?
• How can rehabilitation techniques be used to improve a patient’s quality of life?
• In what ways can biomaterials be used to deliver medications more efficiently?
• What impact does medical virtual reality have on a patient’s care?
• What advancements have been made in the field of neural technology?
• How does nanotechnology pave the way for further advancements in this field?
• What is computational biology and how does it impact our lives?
• How accurate are early diagnosis systems in detecting heart diseases?
• What does the future hold for technology-fueled medications?
• What are the guiding principles of biomedical engineering research?

Read more: Top Biology Research Topics for Academic Writing

Chemical Engineering Research Topics

• How can epoxy resins withstand the force generated by a firing gun?
• The use of software affected design aspects in chemical engineering.
• What challenges are there for biochemical engineering to support health?
• The advancements of plastic technology in the last half-century.
• How can chemical technologies be used to diagnose diseases?
• What are the most efficient pathways to the development of biofuels?
• How can charcoal particles be used to filter water in developing countries?
• Increased production of pharmacy drugs in many countries.
• How do complex fluids and polymers create more sustainable machinery?

Miscellaneous Engineering Research Ideas

• Sensing and controlling the intensity of light in LEDs.
• Design and development of a pressure sensor for a solar thermal panel.
• Development of microsensors to measure oil flow rate in tanks.
• How can organizations achieve success by reducing bottlenecks in the supply chain?
• Research to identify efficient logistics operations within a supply chain.
• Developing frameworks for sustainable assessments taking into account eco-engineering measures.
• Research to identify process improvement plans to support business strategies.
• What can engineers do to address the problems with climate change?
• The impact of training on knowledge performance index within the supply chain industry.
• Research to introduce efficiency within information systems and support the timely transfer of knowledge and information.

Final Words

Out of the 150+ engineering research paper topics and ideas suggested in this blog, choose any topic that is convenient for you to conduct research and write about. In case, you have not yet identified a good topic for your engineering research paper, reach out to us immediately. We have numerous PhD-certified experts in various engineering branches to offer help with research paper topic selection, writing, and editing in accordance with your requirements.

Especially, with the support of our scholarly writers, engineering students of all academic levels can complete their assignments on time and achieve the highest possible grades. Furthermore, taking our engineering assignment help would aid you in submitting high-quality and plagiarism-free research papers with proper citations and supporting evidence.

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I am an Academic Writer and have affection to share my knowledge through posts’. I do not feel tiredness while research and analyzing the things. Sometime, I write down hundred of research topics as per the students requirements. I want to share solution oriented content to the students.

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