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Industrial Engineering: University of Pittsburgh Swanson School of Engineering

Graduate Curriculum and Courses

Graduate Curriculum

The graduate program provides a choice of three main areas of emphasis: information systems, operations research, engineering management or product realization and manufacturing. Additional coursework is available in human factors. The programs are designed to offer the student a wide range of choices. Theoretical and applied subjects are offered with a strong emphasis on solving applied problems.

Specific course requirements for the Master's and Ph.D. programs are described elsewhere on this site.

Students who have an undergraduate background in industrial engineering and demonstrate sufficient knowledge of one or more of these courses may be exempted from the appropriate course and substitute some other, more advanced course for the same. Other courses offered are regularly updated to reflect changes in technology and with the composition of the faculty.

In addition to the listed courses, students may take courses in other departments of the University and Carnegie Mellon University through cross registering.

Course Listing

  • IE 2000 : Fundamentals of Industrial Engineering This course will provide an overview of basic industrial engineering principals, primarily for those students who have not had prior exposure to industrial engineering. Topics will include, but are not limited to, flow charts, work methods, and work measurement including work sampling and most. (1 unit)
  • IE 2001 : Operations Research This is an introductory course in operations research (OR). The primary emphasis is on linear programming and its applications, covering modeling, the simplex method, postoptimality analysis, and the transportation and assignment problems. In addition, the general methodology of operations research and mathematical model building are emphasized. Other areas such as network flows, PERT/CPM, integer programming and goal programming are also covered, with the amount of emphasis depending on the time available. A group project is required.
  • IE 2003 : Engineering Management concepts and processes of qualitative engineering management applied to the management of technical and scientific organizations. Topics include: (1) general systems theory; (2) management and the systems concept; (3) strategic planning and management systems; (4) systems analysis; (5) project management systems; (6) organizational design; (7) evaluation and control of systems; and (8) managing technical professionals.
  • IE 2004 : Data Base Design Introduces the fundamentals required for the design of integrated information systems. Topics on computer hardware including communication networks, workstations/personal computers and automatic identification equipment will be covered. Introduces database concepts, client/server architectures, graphical user interfaces, and design theory for determining functional and systems requirements. Students gain skills in usage of a distributed database management systems and automatic identification equipment such as barcode, magnetic stripe, and radio frequency.
  • IE 2005 : Probability & Statistics for Engineers 1 Probability, random variables, common discrete and continuous probability distributions, expected values, central limit theorem, distributions derived from the normal distribution (x2, t, and f), estimation of parameters and fitting of probability distributions, testing hypothesis and assessing goodness of fit, comparing two samples
  • IE 2006 : Introduction to Manufacturing Systems Emphasizes the technologies and tools required to analyze and design a modern manufacturing system. Topics include pull vs. Push production systems, production processes, material handling systems, process flow analysis, workstation organization, work measurement, setup reduction, cellular layout, production scheduling, and operation certification
  • IE 2007 : Statistics and Data Analysis Analysis of variance, experiments with one factor, experiments with two or more factors, regression analysis, multiple linear regression, response surface methods, analysis of categorical data, nonparametric statistics.
  • IE 2012: Manufacture of Structural Nano-Materials This course covers a number of contemporary research topics on the manufacture and characteristics of high-strength nanostructured materials. In addition, this course emphasizes the nanometer-scale phenomena that make nanostructured materials particularly attractive for structural applications. Relevant topics including dislocation theory, large-strain plasticity phenomena, superplasticity, creep and kinetics of coarsening will be developed from a fundamental level to aid in this elucidation.
  • IE 2015 : Geographic Information Systems This class explores the concepts and history of geographic information systems and teaches students to effectively use the most utilitarian GIS software, ARCGIS.
  • IE 2025 : Facility Layout and Material Handling Introduction to facility layout and location. Topics including activity relationships, space and personnel requirements, computer algorithms for constructing layouts, and both single and multiple facility location methodologies; material handling methods and equipment including conveyors, lift trucks, carousels, automated guided vehicles, and automated storage and retrieval systems are also discussed.
  • IE 2029 : Knowledge Engineering This course covers artificial intelligence (AI) techniques that are based heavily on expert knowledge and how they can be used to improve decision making. Ai systems to be explored may include neural networks, fuzzy systems, symbolic ai, etc. This course will concentrate on model building given the issues and needs of the expert system ant the richness of the data.
  • IE 2030 : Behavioral Systems Engineering Organization theory, effectiveness, structure and design; individual group behavior; motivation; leadership; human behavior in organizations; communication and design systems.
  • IE 2032 : Cases in Systems Management This course involves case analysis with emphasis on design and execution of strategits for technical and scientific organizations. Students are expected to use concepts, knowledge and understanding gained in previous project and engineering management courses to critically evaluate various case situations and participate in classroom discussion. Topics include: introduction and basic project and engineering mgt concepts, scope/integration mgt, schedule/time mgt, cost mgt, quality mgt, contract/procurement mgt, risk mgt, human resource mgt, and communications management.
  • IE 2033 : Board Governance and Management This course captures the new era in enterprise governance, where performance of an organization is shaped and ultimately determined by the characteristics and management of its board of directors. It utilizes the study of boards of directors in contemporary profit an non-profit organizations in conjunction with students’ experiences in leadership roles. Topics covered will include foundation of boards, board structure, info management, communication, and relations with senior management and the function of boards. The course will include case studies and group projects.
  • IE 2034 : Neural Networks and Industrial Applications This course covers the artificial intelligence techniques of neural networks including history, paradigms, hardware and software, applications, and future outlook. Neural networks have been used to address some common problems found in manufacturing and service industries including pattern recognition and classification, predictive modeling, and optimization. The course will also introduce two related techniques—fuzzy systems and genetic algorithms—and discuss how these can be used with neural networks.
  • IE 2037 : Cost Management for Advanced Manufacturing Focuses on current cost management topics such as activity based costing, life cycle costing, target costing, and throughput accounting. Emphasis will be placed on the linkages to advanced manufacturing systems including performance measurement, design, cellular manufacturing, jit, and mrp ii.
  • IE 2039 : Entrepreneurship for Engineers This course considers the development of a new company from inception to "going public." It includes an understanding of accounting principles, budgeting, capital markets, venture capital, operating in the development stage, executive and employee requirements, product development, and growing the company
  • IE 2040 : Advanced Engineering Economy This course considers the development of a new company from inception to "going public". It includes an understanding of accounting principles, budgeting, capital markets, venture capital, operating in the development stage, executive and employee requirements, product development, and growing the company. The course culminates in the group development of a business plan for a new company.
  • IE 2051 : Computer Aided Manufacturing The objective of this course is to develop the framework required for designing, operating, and analyzing automated manufacturing systems. The different areas of cam like numerical control, computer aided process planning, group technology, etc., will be studied. The course is a beginning graduate course and involves a project.
  • IE 2054 : Industrial Robotic Applications This course will focus on the industrial robot as a part of a flexible and automated manufacturing system. It will introduce students to the basic elements of industrial robots and will emphasize knowledge needed to integrate these robots into a larger manufacturing system.
  • IE 2055 : Automation in Manufacturing and Product Design The goal of this course is to gain knowledge in the principles of automating product design and manufacture. Design conceptualization; design for x: manufucturability, assemblability, testability, use, etc. Will be presented. Process planning automation and rapid prototyping will be studied. Students will examine design and manufacturing integration issues as well as typical automated manufacturing equipment. Issued in concurrent engineering and necessary communication networks will also be studied.
  • IE 2058 : Automatic Data Collection Systems The application of automatic data collection (adc) is being incorporated into every aspect of our lives. This is a course teaching knowledge and skills pertinent to the design of various automatic data collection system applications. It includes barcodes, magnetic stripe, machine vision, voice recognition, and wireless data capture. A laboratory component includes exercises in barcode printing and analysis, barcode application development, magnetic stripe encoding and decoding, radio frequency application, inspection using voice recognition, and maching vision.
  • IE 2061 : Ergonomics and Occupational Biomechanics Fundamentals of ergonomics as applied to the industrial workplace. Specific topics include: occupational bio-mechanics, anthropometry, work physiology, cumulative trauma disorders and slip and fall prevention applied to the organization and physical design of the workstation, effects of hand tool design on workers, and analysis of manual material handling jobs.
  • IE 2062 : Data Mining This is an introductory course on data mining. Topics covered include: knowledge representation, classification methods such as decision trees, naive bayesian, covering algorithms, neural networks, instance based learning; association rules; clustering; applications.
  • IE 2073 : Design of Experiments
  • IE 2075 : e-Commerce Tools for Productivity Enterprise software technology, java technology, enterprise systems development life cycle, IT project management.
  • IE 2076 : Total Quality Management The total quality management philosophies of dening, juran, and crosby are the basis for exploring modern concepts of kaizen, quality control, taguchi, evop, etc. The course will include learning the techniques used in tqm as well as gaining an understanding of how major corporations implement tqm programs.
  • IE 2079 : Logistics and Supply Chain Engineering This course will cover the basic elements of the supply chain: procurement, production and distribution. Emphasis will be placed on the decisions pertaining to logistics.
  • IE 2081 : Nonlinear Optimization Solution of simultaneous nonlinear equations; KKT conditions for optimality; unconstrained optimization including search methods, conjugate gradient and variable metric algorithms; convexity and convex programming; constrained optimization including penalty and barrier function methods, Lagrangian algorithms, and primal methods; Lagrangian duality; quadratic, fractional, separable and geometric programming.
  • IE 2082 : Linear Optimization Review of linear algebra, matrices and the simplex methods; revised simplex method; generalized bounds; product form of inverse; pricing and pivot selection; duality and sensitivity analysis; separable programming; linear complementarity; dantzig-wolfe decompositon; column generation; generalized lp; semi-infinite lp, stochastic lp; interior point methods.
  • IE 2084 : Stochastic Processes Reviews probability theory; conditional probability and expectations; discrete-time and continuous time markov chains; poisson process and exponential distributions; renewal theory and its applications; queueing theory; stochastic systems; network of queues.
  • IE 2086 : Decision Models Decision theory, risk and uncertainty, value of information, preference measurements, prioritization of alternatives, multiple objectives and hierarchical decisions.  Case studies are incorporated into lectures.
  • IE 2088 : Digital Systems Simulation Nature of simulation; discrete event simulators; modeling complex systems; input data reduction; random number generation; output data analysis; validation of simulation models; experimental design; variance reduction techniques; comparing alternative systems; overview of simulation languages.
  • IE 2090 : M.S. Project This is the capstone project course for m.s. Students. Students working in teams of 3 or 4 will solve a real world problem in conjunction with a company liaison and a faculty advisor.
  • IE 2098 : Finite Element Analysis in Product Design This course investigates the growing trend of utilizing virtual design and analysis tools in the product development process. A brief overview of the product development process will be given, with particular emphasis on the role of virtual prototyping techniques. In this regard, the underlying theory of the finite element method will be demonstrated through the fundamental concepts of material models, stiffness matrices, loading and boundary conditions, and the generation of stress and displacement results. In addition, utilizing the commercial finite element software package analysis, potential consumer products will be virtual analyzed in an effort to rapidly change and obtain feedback on specific design solutions.
  • IE 2100 : Supply Chain Analysis An overview of Supply Chain Analysis with an emphasis on operations and a strong quantitative orientation. Supply chain strategies; sourcing decisions; demand forecasting; aggregate planning; managing supply and demand; production and inventory control systems including MRP and JIT; dealing with uncertainty; distribution networks; coordination & integration.
  • IE 2101 : Facility Logistics The aim of this course is to study and analyze key factors affecting the productivity of logistics operations and material flows in facilities.  In particular, the course focuses on warehouse and distribution center design and operation including: material handling equipment and system design, order picking, sortation systems, and cross docking.  There is also an investigation of the use of different labor strategies such as bucket brigades.
  • IE 2188 : Simulation Modeling and Applications Introductory graduate course in the concepts, technology and applications of discrete-event and hybrid simulation.  Covers the foundational concepts of simulation and the application of those concepts using commercial software.  Topics include simulation, modeling, validation, input/output analysis, animation, and project success skills. Students will learn to use two simulation products as well as how to conduct/manage simulation projects. Practical experience will be gained in a simulation project
  • IE 2998 : Graduate Projects/Practicum This course is granted as part of the curriculum for work that is done on well defined projects on campus or in the form of an internship in a company, the end result will be a final technical report and a presentation.
  • IE 2997 : M.S. Research
  • IE 2999 : M.S. Thesis
  • IE 3030 : Advanced topics in Engineering Management May cover various topics at the leading edge of technology in the area of engineering management. Course content is announced by the professor.
  • IE 3050 : Advanced topics in Manufacturing May cover various topics at the leading edge of technology in the area of manufacturing. Course content is announced by the professor. (1 unit min / 3 units max)
  • IE 3051 : Computational Optimization This course addresses issues arising in the implementation of optimization algorithms. Computational strategies and techniques will be explored. A major emphasis will be placed on implementing various algorithms for large- scale linear, non linear, and integer programs. Such algorithms include benders' decomposition, dantzig-wolfe decomposition, lagrangian relaxation and algorithms for specially-structured problems.
  • IE 3053 : Global Optimization This is an introductory course to the theory and applications of global optimization. The topics covered in this course include properties of convex/non-convex sets and functions, convex envelopes, duality, local and global optimality conditions, algorithms and their convergence and finiteness, computational complexity of global optimization, cutting planes, outer approximation, convexification, decomposition, branch and bound, D.C. programming, Lipschitzian programming.
  • IE 3058 : E-design of Products and Systems This course is aimed at presenting e-design - a new paradigm which allows designers at distributed remote locations to participate in design of a product directly. It establishes a design paradigm which enables supply chain stakeholders to become active in product design. This new design concept revolutionizes how designers and design software makers relate in the use of various product design tools for product development. Topics to be covered include: introduction to the e-design paradigm; collaborative design; service oriented architecture for e-design; information infrastructure; security and trust in e-design networks; conceptual and embodiment design; dfx and constraint representation; collaborative geometric modeling; collaborative product assembly design; virtual assembly analysis and prototyping; and design optimization.
  • IE 3062 : Advanced Ergonomics A course designed to develop students' knowledge and skills in the areas of ergonomics and occupational biomechanics. The course will teach data acquisition and analysis techniques currently used in ergonomics research and industrial practice. The proposed areas to be covered will be: (1) biomechanical job analysis; (2) electromyographic techniques in the analysis of worker fatigue and injury; (3) metabolic analysis of workers and jobs; (4) strength testing for worker evaluation and placement; and (5) slip and fall analysis and prevention.
  • IE 3075 : Reliability and Maintainability Review of mathematical preliminaries, e.g., stochastic processes, laplace transforms, etc. Combinational reliability, hazard rates and their application, reliability improvement through redundancy and repair, optimization of system reliability, replacement and maintainability policies, software reliability, network reliability, power system reliability, fault trees, introduction to life testing.
  • IE 3076 : Combinatorial Optimization Common combinatorial problems and algorithms, including optimization algorithms and heuristics. Topics may include: max-flow, matching, primal-dual algorithms, matroids, integer programming, cutting planes, tsp.
  • IE 3077 : Therapeutic Optimization Seminar This seminar surveys current research in therapeutic optimization. Emphasis is placed on critiquing and extending the current state of the art. Students will also be expected to present their own work in class.
  • IE 3078 : Convex Optimization This course develops a modern framework for convex optimization. The topics covered in this course include concepts of convex analysis, smooth convex optimization, nonsmooth convex optimization, structural optimization, duality theory.
  • IE 3080 : Advanced topics in Operations Research May cover various topics at the leading edge of technology in the area of operations research. Course content is announced by the professor.
  • IE 3081 : Numerical Optimization Project-oriented course concerned with detailed computer implementation of an optimization algorithm. Each student will select a separate algorithm.
  • IE 3082 : Scheduling Models In-depth study of the theory of scheduling models. Material includes single-machine models, multi-machine models, heuristic models and rule-based models. Problems in workforce scheduling are also covered.
  • IE 3084 : Operations Research Models in Production This is a course on operations research models in production planning, scheduling and inventory control. The course is meant for doctoral and advanced master's students, and its emphasis will be on theoretical and modeling issues. The first half of the course will be in the nature of a survey of seminal work in this area. The second half will be based primarily upon journal articles in the literature and will address research issues. In addition, all students will be expected to undertake and complete a project for the course.
  • IE 3085 : Queuing Theory Simple queuing models using Markov processes. Network series and cyclic queues. Models with general arrival or service patterns. Closed queues. Numerical and simulation techniques.
  • IE 3087 : Network-based Optimization This course covers graphs, digraphs and related concepts, node and edge covering problems, euler tours, hamiltonian cycles, tsp, set covering and matching problems, shortest path problems, maximum flow problems and minimum cost network flow problems.
  • IE 3088 : Integer Programming Polyhedral theory, computational complexity, superadditive duality, and integral polyhedra.
  • IE 3089 : Repairable Systems Modeling and Analysis A repairable system is a system that can be restored to a satisfactory condition through some intervention by a decision maker.  In a manufacturing setting, such actions might include inspections, part replacements or setting adjustments; in a medical context, such actions might include disease screening, surgery or drug therapy.  In this course, we consider applications of probability, simulation and optimization in the: (a) mathematical modeling of the performance of repairable systems, and (b) designing of optimal inspection and maintenance policies for repairable systems. 
  • IE 3091 : Heuristic Optimization This course covers methods of heuristic optimization including genetic algorithms, simulated annealing and tabu search. Both continuous and discrete optimization domains are considered with emphasis on np complete combinatorial problems found in engineering and production. Solution encodings, local and global search methodologies, stochastic aspects and convergence are discussed.
  • IE 3093 : Stochastic Programming This course considers stochastic programming, a technique for making optimal decisions under uncertainty. Will consider theory, algorithms and applications. Extensions to multi-stage problems and stochastic integer programs will be discussed.
  • IE 3094 : Markov Decision Processes Introduces the fundamentals of discrete sequential models when outcomes are uncertain. Covers formulation and analysis of stochastic dynamic programs under several objective criteria; developing and enhancing solution algorithms; applications in the areas of inventory control, vehicle routing, and resource allocation; development of approximate solution techniques.
  • IE 3095 : Graduate Seminar Speakers from universities and industry discuss research topics and state-of-the-art material in the areas of operations research, engineering management, and manufacturing systems. Enrollment in this course is mandatory for all full-time graduate students. (1 unit)
  • IE 3096 : Topics in Financial Engineering The main goal is to develop insight into the analysis of modern financial instruments and markets by means of: (1) term structures; intertemporal exchanges, interest late calculus, the zero curves, and approximation theory, the expectation hypothesis; (2) asset price dynamics under stochastic uncertainty; binomial lattice models, lp duality and martingales, random walks, weiner processes and stock price models, the black-scholes calculus, replicating portfolios, entropy and goal programming illustrations; (3) asset pricing under uncertainty with perturbations.
  • IE 3097 : Algorithms for Engineers This course will develop student's ability to understand algorithms and use them appropriately for real-world and theoretical problems. Examples will be taken from IE applications and may also be tailored to students' interests. Topics covered will include complexity theory, running times and performance measures, common ideas in algorithms, randomized algorithms, approximation algorithms, parallel processing and consequences of float-point arithmetic. At the end of the course, students will be prepared to further pursue topics on their own through additional course work.
  • IE 3098 : Advanced Topics in Markov Decision Processes This course covers current topics in Markov decision processes, including stochastic games, partially observed MDPs, robust MDPs, risk-sensitive MDPs, and approximation techniques.

For more information contact gradie@engr.pitt.edu

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