Industrial Engineering

Website

Hanchen Huang, PhD
Professor and Chair

Nader Jalili, PhD
Professor and Associate Chair for Graduate Studies and Research

334 Snell Engineering Center
617.373.2740
617.373.2921 (fax)
Tess Waggett, Business Manager, tess.waggett@northeastern.edu

The Department of Mechanical and Industrial Engineering (MIE) offers comprehensive research and educational programs for both Master of Science (MS) and Doctor of Philosophy (PhD) students in both traditional mechanical and industrial engineering disciplines, as well as applied programs. Our cutting-edge and vibrant doctoral programs include industrial engineering and interdisciplinary PhD programs; while our master's degree programs consist of both master's degrees in industrial engineering and operations research. These extensive programs and concentrations allow for the selection of a degree that meets a wide variety of personal and professional goals.

Master of Science Degree

To be eligible for admission to any of the MS degree programs, a prospective student must hold a Bachelor of Science degree in engineering, science, mathematics, or an equivalent field. Students in all master’s degree programs must complete a minimum of 32 semester hours of approved course work (exclusive of any preparatory courses) with a minimum GPA of 3.000 (see table below). Students may pursue any master's program either on a full-time or part-time basis; however, certain restrictions may apply.

Degree Requirements Course Work Only With Project With Thesis
Required core courses 16 SH 16 SH 16 SH
Elective courses 16 SH 12 SH 8 SH
MEIE 6800 Technical Writing N/A 0 SH 0 SH
MEIE 6850 Research Seminar in Mechanical and Industrial Engineering N/A 0 SH 0 SH
Project/thesis 0 SH 4 SH 8 SH
Minimum semester hours required 32 SH 32 SH 32 SH

Graduate Certificate Options

Students enrolled in a master's degree in Industrial Engineering have the opportunity to also pursue one of 14 engineering graduate certificate options in addition to or in combination with the MS degree. Students should consult their faculty advisor regarding these options.

Gordon Institute of Engineering Leadership Option

Students have the opportunity to pursue the Gordon Engineering leadership program in combination with the MS degree.

Doctor of Philosophy Degree

The MIE department admits applicants to the PhD program in industrial engineering either directly after earning a suitable bachelor’s degree (Direct Entry) or after earning a master’s degree (Advanced Entry). Upon acceptance into the program, an applicant is designated as a doctoral student. This designation is changed to doctoral candidate upon successful completion of the doctoral qualifying examinations (both written and oral area exams) and all the required course work. The PhD is awarded to students who demonstrate high academic achievement and research competence in the fields of mechanical or industrial engineering. The MIE department expects all successful doctoral candidates to show depth of knowledge and research innovation in their chosen field of specialization. 

Doctor of Philosophy (PhD)

Master of Science in Industrial Engineering (MSIE)

Graduate Certificate

Industrial Engineering Courses

IE 5374. Special Topics in Industrial Engineering. 4 Hours.

Offers topics of current interest in industrial engineering. Prereq. Junior, senior, or graduate standing; engineering students only.

IE 5400. Healthcare Systems Modeling and Analysis. 4 Hours.

Discusses the key functions of healthcare operations management, such as patient and process flow, process improvement, facility layout, staffing and scheduling, capacity planning, and resource allocation. Focuses on analysis, design, management, and control of health systems and processes that are necessary to provide clinical care. The applications of systems engineering methods, such as optimization, simulation, and queuing models, are discussed through papers and case studies in different care settings (e.g., hospitals, emergency departments, surgery departments, and outpatient clinics) for different diseases (e.g. diabetes, cancer, mental health, cardiovascular disease). Uses spreadsheet tools to model and solve simulation and optimization problems. Prereq. IE 4515, OR 6205, or equivalent and junior, senior, or graduate standing.

IE 5500. Systems Engineering in Public Programs. 4 Hours.

Introduces the design, development, analysis, and application of mathematical modeling for addressing public programs and societal needs. Systems engineering and mathematical models form the basis for decision making in both public and private applications. Focusing on societal applications, offers students an opportunity to discover how to incorporate public objectives and characteristics of large systems in the development of models and policies. Examines applications in the operation of public programs (e.g., public health systems, government programs) and public safety (e.g., security, emergency preparedness, and disaster response). Modeling techniques include game theory, data envelopment analysis, cost-benefit analysis, simulation, differential equations, and stochastic optimization. Prereq. (a) IE 4515, OR 6205, or equivalent and (b) IE 3412, IE 6200, or equivalent and (c) junior, senior, or graduate standing.

IE 5617. Lean Concepts and Applications. 4 Hours.

Designed to give students an understanding of the fundamentals of lean thinking and train them in applying this knowledge to practical problems. Uses case studies from different disciplines to help students learn lean principles and develop skills to implement them in practice. Covers theory and applications of lean six sigma, in which lean focuses on waste reduction while six sigma strives to eliminate defects. A knowledge-driven and customer-focused approach to creating value, lean thinking calls for process changes to eliminate waste, shorten product delivery time, improve product quality, and curtail costs. Key tenants of lean thinking are value, value stream, flow, pull, and perfection. Lean thinking is imperative for organizations aspiring to stay competitive by creating and delivering products in less time while improving customer satisfaction. Prereq. Junior, senior, or graduate standing.

IE 5620. Mass Customization. 4 Hours.

Provides students with conceptual understanding and implementation strategies of mass customization (MC). MC is both a business and production paradigm where a company provides the customers with goods and services that suit their individual needs but does so with the efficiency and costs of mass production. MC is important in many sectors including computers, automotive, healthcare, banking, insurance, and tourism. It is based on principles of industrial engineering, mechanical engineering, management science, and marketing. Topics include typology of mass-customized production systems, manufacturing processes for MC, information needs of MC, customer focus, marketing issues, technology enablers, implementation methods, and case studies. Methodology includes lectures, case discussions, plant visits, guest lectures, and a term project. Cross-disciplinary activities, particularly between engineering and business students, are encouraged wherever possible. Prereq. Junior, senior, or graduate standing.

IE 5630. Biosensor and Human Behavior Measurement. 4 Hours.

Emphasizes the measurement of human behavior in complex human-machine interaction. Topics include introduction of complex human-machine interactions; research methods in complex human-machine interactions; various kinds of human psychophysiological signals/cues, including physiological cues, facial expressions, eye-gaze movement, head movement, contextual cues; human cues and behavior relationship; transducers and measurement for these human cues/signals; basic principles of biosensors; general classification of biosensors; current technologies for building biosensors; conventional transducers and new technologies including micro-/nanotechnology; general systematic design process for biosensors; application of biosensors to understand human behavior in human-machine interactions. Also introduces the latest relevant research advancements in sensor fusion, affective computing, and emotion recognition. Prereq. Junior standing or above; engineering students only.

IE 5640. Data Mining for Engineering Applications. 4 Hours.

Introduces data mining concepts and statistics/machine learning techniques for analyzing and discovering knowledge from large data sets that occur in engineering domains such as manufacturing, healthcare, sustainability, and energy. Topics include data reduction, data exploration, data visualization, concept description, mining association rules, classification, prediction, and clustering. Discusses data mining case studies that are drawn from manufacturing, retail, healthcare, biomedical, telecommunication, and other sectors. Prereq. (a) IE 3412, MATH 3081, or IE 6200 and (b) junior, senior, or graduate standing.

IE 5976. Directed Study. 1-4 Hours.

Offers theoretical or experimental work under the direction of members of the department on a chosen topic. Course content depends on instructor. Prereq. Junior, senior, or graduate standing.

IE 5978. Independent Study. 1-4 Hours.

Offers theoretical or experimental work under individual faculty supervision. Prereq. Junior, senior, or graduate standing.

IE 5984. Research. 1-4 Hours.

Offers an opportunity to conduct research under faculty supervision. Prereq. Junior, senior, or graduate standing.

IE 6200. Engineering Probability and Statistics. 4 Hours.

Studies fundamental concepts of probability. Topics include events, sample space, and discrete and continuous random variables; density functions, mass functions, cumulative probability distributions, and moment generating functions; expectation of random variables; common discrete and continuous probability distributions including binomial, Poisson, geometric, uniform, exponential, and normal; multivariate probability distributions, covariance, and independence of random variables; sampling and descriptive statistics; and parameter estimation, confidence intervals, and hypothesis testing. Also introduces analysis of variance. Prereq. Knowledge of multivariate calculus; engineering students only.

IE 6300. Manufacturing Methods and Processes. 4 Hours.

Focuses on manufacturing and its relationship to design and computers. Examines the relationship between design and various aspects of manufacturing. Covers manufacturing systems, manufacturing processes, bill of materials, group technology, mechanical tolerancing, QC, SPC, QPC, TQM, process planning and CAPP, NC part programming, supply chain management, production scheduling, JIT, lean manufacturing, flexible manufacturing systems, CIM cells, and manufacturing control via, say, programmable logic controllers. Prereq. Engineering students only.

IE 6962. Elective. 1-4 Hours.

Offers elective credit for courses taken at other academic institutions.

IE 6964. Co-op Work Experience. 0 Hours.

Provides eligible students with an opportunity for work experience. Prereq. ENCP 6000.

IE 6965. Co-op Work Experience Abroad. 0 Hours.

Provides eligible students with an opportunity for work experience abroad. Prereq. Engineering students only.

IE 7200. Supply Chain Engineering. 4 Hours.

Presents modern quantitative techniques for designing, analyzing, managing, and improving supply chains using deterministic and probabilistic models. Topics include a macro view of supply chains, demand forecasting, aggregate planning, sequencing and scheduling, inventory analysis and control, materials requirement planning, pricing and revenue management, contracts decisions, transportation decisions, location and distribution decisions, supplier selection methods, and global supply chains. Prereq. (a) IE 6200 with a grade of C or MATH 7241 with a grade of C and (b) OR 6205 with a grade of C; restricted to students in the College of Engineering and in the College of Science.

IE 7215. Simulation Analysis. 4 Hours.

Covers elementary queueing models, simulation and modeling, simulation model design, a survey of simulation languages with one language covered in detail, input data analysis and distribution fitting, model verification and validation, output analysis and transient/steady-state response, terminating/nonterminating systems, model experimentation and optimization, random number/random variate generation, and variance reduction techniques. Prereq. IE 6200 with a grade of C or MATH 7241 with a grade of C; restricted to students in the College of Engineering and in the College of Science.

IE 7255. Manufacturing Processes. 4 Hours.

Covers the structures of metals, polymers, and ceramics and their manufacturing processes. Manufacturing processes include casting, forming, machining, welding, molding, and particulate processing. Discusses nontraditional manufacturing processes including electrical discharge machining, laser machining, and water jet machining. Also covers manufacturing processes for the electronics industry, such as processing integrated circuits, and electronic assembly and packaging. Prereq. Engineering students only.

IE 7270. Intelligent Manufacturing. 4 Hours.

Covers several advanced and contemporary topics in manufacturing. Includes applications of computational methods including experts systems, neural networks, and multiagents in manufacturing. Discusses the methods related to distributed and Web-enabled manufacturing. Prereq. Restricted to students in the College of Engineering and in the College of Science.

IE 7275. Data Mining in Engineering. 4 Hours.

Covers the theory and applications of data mining in engineering. Reviews fundamentals and key concepts of data mining, discusses important data mining techniques, and presents algorithms for implementing these techniques. Specifically covers data mining techniques for data preprocessing, association rule extraction, classification, prediction, clustering, and complex data exploration. Discusses data mining applications in several areas, including manufacturing, healthcare, medicine, business, and other service sectors. Prereq. IE 6200 with a grade of C, MATH 7241 with a grade of C, or permission of instructor; restricted to students in the College of Engineering and in the College of Science.

IE 7280. Statistical Methods in Engineering. 4 Hours.

Discusses statistical models for analysis and prediction of random phenomena. Topics include review of descriptive statistics and hypothesis testing, linear models, both regression and ANOVA. Introduces design of experiments. Covers experiments with single and multiple factors of interest, and considers experiments with high-order experimental restrictions. Prereq. IE 6200 with a grade of C or MATH 7241 with a grade of C; restricted to students in the College of Engineering and in the College of Science.

IE 7285. Statistical Quality Control. 4 Hours.

Designed to study the fundamental concepts of quality planning and improvements. Studies analysis and application of modern statistical process control methods including cusum, EWMA, multivariate, and modified control charts. Covers inspection error and design of sampling plans. Topics include software quality assurance, and study of the concepts of Deming, Ishikawa, Feigenbum, and Taguchi’s approach in quality planning, organization, and improvement. Prereq. IE 6200 with a grade of C or MATH 7241 with a grade of C; restricted to students in the College of Engineering and in the College of Science.

IE 7290. Reliability Analysis and Risk Assessment. 4 Hours.

Studies principles of the methods of risk assessment and reliability analysis including fault trees, decision trees, and reliability block diagrams. Discusses classical, Bayesian, and median rank methods for analysis of components and systems reliability. Presents various factors that determine the stress and strength of components and their impact on system reliability. Uses practical applications, examples, and problems to cover a broad range of engineering fields, such as mechanical, electrical, industrial, computer, structures, and automatic control systems. Prereq. IE 6200 with a grade of C or MATH 7241 with a grade of C; restricted to students in the College of Engineering and in the College of Science.

IE 7315. Human Factors Engineering. 4 Hours.

Offers students an opportunity to acquire the necessary knowledge and skills to recognize and analyze existing or potential human factors problems and to identify, design, and possibly implement feasible solutions. Includes introduction to human factors and ergonomics; engineering anthropometry and biomechanics; physiology related to human factors and workstation design; cognition and information processing; decision making, attention, and workload; human error and accidents; human-machine interface design; controls and displays; and human factors applications in transportation, aerospace, consumer product design, and so forth. Prereq. Restricted to students in the College of Engineering and in the College of Science.

IE 7374. Special Topics in Industrial Engineering. 4 Hours.

Offers topics of interest to the staff member conducting this class for advanced study.

IE 7440. Industrial Engineering Leadership Challenge Project 1. 4 Hours.

Offers students an opportunity to develop and present a plan for the demonstration of a marketable technology product or prototype with an industrial-engineering focus. Constitutes the first half of a thesis-scale project in technology commercialization. Requires work/training with a sponsoring organization or employer to improve a process or develop a project that is of significant value to the organization and demonstrates a quantifiable market impact while enhancing the student’s technological and engineering depth and fostering the student’s leadership development. Prereq. Industrial engineering/engineering leadership students only.

IE 7442. Industrial Engineering Leadership Challenge Project 2. 4 Hours.

Continues IE 7440, further developing a thesis-scale project in technology commercialization. Offers students an opportunity to demonstrate their development of a marketable technology product or prototype with an industrial engineering focus and produce a written documentary report on the project to the satisfaction of an advising committee. Requires work/training with a sponsoring organization or employer to improve a process or develop a project that is of significant value to the organization and demonstrates a quantifiable market impact while enhancing the student’s technological and engineering depth and fostering the student’s leadership development. Prereq. IE 7440; industrial engineering/engineering leadership students only.

IE 7615. Neural Networks in Engineering. 4 Hours.

Covers the theory and applications of neural networks in engineering. Reviews basics of machine learning, discusses important neural network architectures, and presents neural network training methods and algorithms. The specific neural network models covered in this course include feedforward neural networks, radial basis function networks, support vector machines, self-organizing feature maps, and recurrent networks. Discusses neural network applications in several areas including manufacturing, healthcare, medicine, business, and diagnostics and prognostics. Prereq. Restricted to students in the College of Engineering and in the College of Science.

IE 7945. Master’s Project. 4 Hours.

Offers theoretical or experimental work under individual faculty supervision.

IE 7962. Elective. 1-4 Hours.

Offers elective credit for courses taken at other academic institutions.

IE 7978. Independent Study. 1-4 Hours.

Offers theoretical or experimental work under individual faculty supervision. An independent study must be petitioned and approved by the academic advisor. The petition must clearly state the reason for taking the course; a brief description of goals; as well as the expected outcomes, deliverables, and grading scheme. Master’s degree students in thesis or project options are not eligible to take independent study.

IE 7990. Thesis. 1-8 Hours.

Offers analytical and/or experimental work conducted under the direction of the faculty in fulfillment of the requirements for the degree. Requires first-year students to attend a graduate seminar program that introduces the students to the methods of choosing a research topic, conducting research, and preparing a thesis. Requires successful completion of the seminar program.

IE 7994. Thesis Continuation—Part Time. 0 Hours.

Continues thesis work conducted under the supervision of a departmental faculty member.

IE 7996. Thesis Continuation. 0 Hours.

Continues thesis work conducted under the supervision of a departmental faculty member.

IE 8960. Candidacy Preparation—Doctoral. 0 Hours.

Offers students an opportunity to prepare for the PhD qualifying exam under faculty supervision. Prereq. Intended for students who have completed all required PhD course work and have not yet achieved PhD candidacy; students who have not completed all required PhD course work are not allowed to register for this course.

IE 8964. Co-op Work Experience. 0 Hours.

Provides eligible students with an opportunity for work experience.

IE 8986. Research. 0 Hours.

Offers students an opportunity to conduct full-time research under faculty supervision.

IE 9000. PhD Candidacy Achieved. 0 Hours.

Indicates successful completion of program requirements for PhD candidacy.

IE 9986. Research. 0 Hours.

Offers students an opportunity to conduct full-time research under faculty supervision.

IE 9990. Dissertation. 0 Hours.

Offers dissertation supervision under individual faculty supervision. May be taken twice for course credit. Prereq. PhD candidacy in industrial engineering.

IE 9996. Dissertation Continuation. 0 Hours.

Offers continuing dissertation supervision under individual faculty supervision. Prereq. IE 9990 completed twice; industrial engineering students only.