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Graduate Calendar
Spring 2009

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Courses offered by Industrial and Manufacturing Systems Engineering at the graduate level are listed below. Students may take courses from outside Industrial and Manufacturing Systems Engineering with permission of the Chair of the Graduate Program and the advisor.

All courses listed will not necessarily be offered in any given year.

91-500. Optimization
Classical theory of optimization. Kuhn-Tucker conditions. Unconstrained optimization; gradient methods, conjugate gradient methods, variable metric methods, search techniques. Constrained optimization. Approximation methods, projection methods, reduced gradient methods; penalty function methods; computational algorithms. Recent advances in optimization. Use of computer software packages. (Prerequisite: 91-312 or equivalent.) (3 lecture hours a week.)

91-501. Industrial Experimentation and Applied Statistics
Distributions of functions of variables, estimations and tests of hypotheses, power of tests, non-parametric tests, sampling techniques, analysis of variance, randomized blocks. Latin squares and factorial experiments. (Prerequisite: 91-227 or equivalent.) (3 lecture hours a week.)

91-502. Manufacturing Systems Simulation
Discrete-event system simulation. Random number generation. Stochastic variate generation. Input parameters; identification and estimation. Output analysis. Static and dynamic output analysis; initial and final conditions; measures of performance and their variance estimation; confidence interval. Design of experiments. Various sampling techniques. Single and multifactor designs. Fractional designs. Response surfaces. Regeneration method for simulation analysis; Monte Carlo optimization. (3 lecture hours a week.)

91-503. Production and Inventory Control Systems
Analysis of production-inventory systems. Inventory systems; deterministic, single-item and multi-item models; quantity discounts; stochastic, single-period models; periodic review and continuous review models. Production planning. Static demand models; product mix and process selection problems; multi-stage planning problems. Dynamic demand models; multi product and multistage models. Operations scheduling; job shop scheduling; line balancing. New directions in production systems research. (Prerequisite: 91-413 or equivalent.) (3 lecture hours a week.)

91-504. Advanced Operations Research I
Theory and computational techniques for solving linear and integer programming problems. Theoretical foundations of the simplex algorithm. Duality and sensitivity analysis. Network flow methods. Integer programming problems. Branch and bound methods, implicit enumeration methods, cutting plane methods. Interior point methods and other recent developments. (Prerequisite: 91-312 or equivalent.) (3 lecture hours a week.)

91-505. Advanced Operations Research II
Probabilistic O.R. models. Markovian decision process. Queueing theory. Single channel and multichannel queueing systems. Queues with general arrival and service patterns. Bulk queues and priority queues. Applications of queuing models. Probabilistic dynamic programming. (Prerequisite: 91-412 or equivalent.) (3 lecture hours a week.)

91-506. Computer-Aided Modeling of Complex Surfaces
This course provides an understanding of complex surfaces and their applications, design, mathematical modeling and manipulation techniques. It provides a mathematical foundation of sculptured surfaces, with emphasis on NURBS. Topics include: Geometric modeling, Curves and surfaces representation, B-Spline basis functions, Rational B-Splines curves, and surfaces, Construction of NURBS surfaces, Development of prototype complex surfaces using CAD software and MATLAB, and Introduction of reverse engineering of complex surfaces, modeling, manipulation and prototyping. (Prerequisite: 06-91-311 and 91-315, or equivalent.) (3.0 Lecture hours per week)

91-507. Advances in Industrial Ergonomics
Ergonomics and work design; human workload measurement in industry; visual display terminals at the workplace; signal detection and visual inspection; user-computer interaction; human factors aspects of flexible manufacturing systems; effects of individual and combined environmental stressors on human performance. (Prerequisite: 91-415 or equivalent.) (3 lecture hours a week.)

91-508. Reliability Engineering
Basic reliability distributions. Constant failure rate models-exponential reliability function, Poisson process. Time dependent failure models-the Weibull, normal, log-normal distributions. State-dependent systems-Markov analysis. System reliability-system structure function. Reliability growth testing-noon-parametric methods, censored testing and accelerated life-testing. Design for reliability-specification, reliability allocation, failure analysis, system safety. Maintainability and availability. (Prerequisite: 91-327 or equivalent.) (3 lecture hours a week.)

91-509. Computer-Integrated Manufacturing
Development of CIM; the CIM pyramid-key functions. System integration; standards for communications-MAP. Data base as the hub of CIM-types of data base. Role of simulation and support systems-decision support systems and expert systems. Sensor technology, robot vision, and group technology. Impact of CIM. Factory of the future. (Prerequisite: 91-411 or equivalent.) (3 lecture hours a week.)

91-510. Advanced Engineering Economy
Principles and methods for engineering analysis of industrial projects and operations. Criteria for economic decisions, project investment analysis, gain and loss estimating and techniques for economic optimization under constraint are included. Emphasis is placed on the construction and use of analytical models in the solution of engineering economy problems. Elements of risk and uncertainty are included through use of probabilistic techniques. (Prerequisite: 85-313 or equivalent.) (3 lecture hours a week.)

91-511. Stochastic Processes
Stochastic processes. The Poisson process-relationship to exponential, Erlang and uniform probability distributions. Markov chains-basic limit theorem. Continuous time Markov chains - birth-and-death processes, time-dependent probabilities, limiting probabilities, relationship to the exponential distribution, uniformization. Renewal theory-limit theorems, renewal reward processes, regenerative processes, computing the renewal function. Brownian motion and stationary processes. (Prerequisite: Statistics 91-412 or equivalent.) (3 lecture hours a week.)

91-512. Manufacturing Systems Paradigms
Manufacturing systems paradigms (including DML, Batch, Cells, FMS & RMS), components, characteristics, automation, operation, planning and control. Changeability and mass customization. Integrated products/systems design, process planning, GT & CIM. Special topics: Assembly, Robotics, Inspection, Quality and Cost.” (Prerequisite: 91-413, or equivalent / permission of instructor). (3 lecture hours a week)

91-514. Engineering Design, Methodology & Applications
Engineering Design is a creative, iterative and often open-ended process subject to constraints. Topics include: design creativity & problem solving, engineering conceptual design & embodiment design, practices for product realization design theories and methodologies, parametric design, probabilistic design, industrial design, design and manufacturing integration, concurrent Enginneering, materials selection in design, design for x (e.g. manufacturing, assembly), engineering design communication. Significant time is devoted to the applications of design theories and methodologies and to a product/process design realization. (3 lecture hours a week.)

91-515. Artificial Intelligence Applications in Manufacturing
The objective of this course is to teach graduate students how artificial intelligence techniques can be applied to manufacturing operations. Detailed topics to be discussed in this course include: basic knowledge representation methods and problem solving techniques; different search algorithms; introduction to AI high level languages; introduction to the CLIPS shell; AI application in Design; AI application in Operation Management; AI application in Diagnosis; and, AI application in Control. (Prerequisite: 91-503 or 91-504 or equivalent.) (3 lecture hours a week.)

91-516. Computer-Aided Design (CAD)
This course will focus on computer-aided methods and applications. The lectures present basic and generic principles and tools, supplemented with significant hands-on practice and engineering applications. Various topics are studied and practiced using CAD/CAE software, such as Engineering design and the role of CAD, geometric modelling systems, representation of curves and surfaces, surface modelling, solid modelling and applications, parametric representations, assembly modelling, computer-aided engineering (CAE) and applications, distributed collaborative design, and digital mock-up. (Prerequisite: 91-411 or equivalent.) (2 lecture hours a week and 2 laboratory hours a week.)

91-517. Automotive Assembly Work Measurement
A Graduate study of manufacturing driven product designs, assembled in a human orientated workplace. Learn the science of work measurement to continuously evaluate existing designs against internal and external better practices and utilize insights gained from hands-on product teardowns in the development of innovative patentable ideas & product redesign proposals that support the lean enterprises balance scorecard. (9 Hours Per Week + 4.5 Laboratory Hours Per Week, For 4 weeks)

91-518. Manufacturing Systems: Modelling, Analysis and Performance Measures
This course is specifically oriented toward performance issues that arise in Automated Manufacturing Systems (AMS). The main goal of this course is to introduce efficient analytical modeling tools. Examples related to serial manufacturing systems. Flexible Manufacturing Systems will be presented to illustrate the theory and applications of these modeling tools. The reliability and maintainability techniques are also presented and integrated in the design, the analysis and the modeling of AMS. (Pre-requisites: 06-91-312 or equivalent and Probability and Statistics)(3 Lecture Hours Per Week)

91-519. Work Organization: Analysis and Design
Introduction to the applications of organization theory for the analysis and design of work organizations (industrial enterprises). Assessment and improvement of organizations through integration of social and technical systems in order to achieve organizational purpose. Fundamentals of organization structure. Classical organization theories. Group decision processes (group and individual). Organizational culture and ethics. Organizations and manufacturing technology. Management of knowledge workers. Information and communication technologies in program in organizations. Innovation and creativity, change management. Organizational accidents and errors, risk management. Impact of globalization and international environment on organizational strategies. (Pre-requisite: Graduate Standing in Engineering or Business) (3 Lecture Hours Per Week)

91-520. Engineering Applications in Health Care
Introduction to the broad range of current technological and organizational issues in health care. Overview of health care industry. Instrumentation for medical diagnostics (biomedical sensors, medical imaging). Medical diagnostics and decision making. Information technology in health care (information systems, electronic medical records). Principles of evidence-based medicine. Medical studies and statistics. Prosthetics and orthotics. Lab automation and surgical robotics. Manufacturing in health care. Health care facilities planning and design. Quality management in health care. (Prerequisites: graduate standing in engineering, business, nursing or human kinetics; 3 lecture hours a week).

91-521. Sustainable Manufacturing
The objective of this course is to introduce students to how the environment has been affected by the activities of the manufacturing industry and how this type of impact could be measured and reduced. Students will learn to identify design and manufacturing issues related to the environment. Topics discussed in this course include sustainable development, sustainability, environmentally conscious design and manufacturing concepts and practices, recycling and reuse, material selection and compatibility, de-manufacturing and re-manufacturing, life-cycle assessment, and ISO 14000.( 3 Lecture Hours Per Week)

91-522. Supply Chain Management and Logistics
This course covers the major issues associated with the management of Supply Chain and Logistics, covering both technical and managerial issues with emphasis on the analytical decision support methods and tools. Topics include supply chain network design, inventory models and theories, transportation and logistics planning, outsourcing and pricing, and case study. (Pre-requisite: 91-312 or 91-390, or equivalent) (3 Lecture Hours Per Week)

91-523. Product Innovation and Design Management
This course covers the critical factors affecting product development and innovation and identifies the common characteristics of successful new products drawing upon best industrial practice. The aim is to provide students with an understanding of the managerial and technical processes commonly involved in product development and innovation. Three main themes will be covered throughout this course: Product Design and Innovation; Idea Generation Techniques; Design and Innovation Project Management. (3 Lecture Hours Per Week)

91-524. Advanced Topics in Discrete Optimization
This course is concerned with topics in discrete optimization, particularly in integer programming theory and techniques. Topics include: Analysis of algorithms, modeling and applications of discrete optimization, dynamic programming, branch and cut, Lagrangian duality, modern meta-heuristic methods, introductions to nonlinear integer programming and stochastic (integer) programming, software for solving discrete program, advances in discrete optimization. (Pre-requisite: 06-91-312 or equivalent.) (3 Lecture Hours Per Week)

91-590. Special Topics
Selected advanced topics in the field of Industrial Engineering. (3 lecture hours a week.)

91-595. Graduate Seminar
Presentations by graduate students, staff, and visiting scientists on current research topics. Graduate students are required to register and give a presentation in the semester prior to thesis defence. All graduate students are expected to attend each and every seminar and no less than 75% of all seminars. This course will be graded on a Pass/Fail basis. (1 lecture hour a week.)

91-796. Major Paper

91-797. Thesis

91-798. Dissertation