Introduction to the theory and methods to design and analyze systems. Problem identification, description, modeling, information systems, solution and implementation, project management, presentation techniques, report writing, work design and measurement, and work measurement techniques.
Introduction to manufacturing history and an overview of manufacturing technologies and future trends (e.g., product design, semiconductor and electronics manufacturing; computer manufacturing; metal forming and machining, plastic injection molding, micro-machining, and biotechnology in manufacturing).
Introduction to engineers transitioning into management: engineering managerial functions; planning and organizing technical activities; motivation of individuals and groups; team building; leadership; power and influence; decision making; communications; conflict resolution and project management using a software package.
Analysis and design of work systems considering human capabilities and limitations, human anatomy and physiology, interacting with physical environment, and occupational safety and health. Overview of physical ergonomics, safety, hygiene, and cognitive ergonomics.
An applications-oriented course using statistical software for formulating and solving engineering statistical problems. Descriptive statistics, probability distributions, variability, sampling, confidence intervals, tests of significance, and design of experiments.
Application of deterministic operations research techniques: linear programming, transportation problems, assignment problems, integer programming. Model formulation and problem solving using a computer package.
A key component of the course is a design project.
Basic principles of computer-aided manufacturing and technologies impacting the product development cycle. Potential topics: software and hardware of numerical control machines, robotics, computer control of manufacturing processes and systems, rapid prototyping, and solid modeling.
Introduction to jurisprudence, civil procedure, contract, product liability, employment, real property, intellectual property, alternative dispute resolution, and other fields of law relevant to the engineering profession.
Theory and practice of decision making under uncertainty. Graphical modeling techniques including influence diagram and decision trees. The value of information. Utility theory foundations, risk preference, and multi-attribute decision modes. Economic justification of projects.
Systematic analysis of processes through the use of statistical analysis, methods, and procedures; statistical process control, sampling, regression, ANOVA, quality control, and design of experiments. Use of software for performing a statistical analysis.
Foundations of Radio Frequency Identification Systems (RFID). The fundamentals of how RFID components of tab, transponder, and antennae are utilized to create RFID systems. Best practices for implementation RFID systems in common supply chain operations.
General consideration in tool designing, design of tool and workholding devices, forming machines and presswork tools; application of computer graphics and finite element techniques, and prediction of tool paths in CNC machines.
Foundations of supply chain network modeling. The concepts that support the economic and service trade-offs in supply chain and logistics management. Using decision support system (DSS) to design optimal logistics network models given data requirements and operational parameters. Using leading software packages to model problems arising in strategic management of logistics networks.
The process of planning, implementing and controlling the efficient, effective flow and storage of goods, services and related information from the point of origin to the point of consumption. Domestic transportation systems, distribution centers and warehousing, international logistics, logistics system controls, and reengineering logistics systems.
Senior or junior standing, admission to the University Honors Program.
Independent research project conducted under the guidance of a faculty member in the Department of Industrial and Management Systems Engineering. Research should contribute to the advancement of knowledge in the field. Written thesis and formal presentation are required.
Liability issues arising out of manufacturing defects, design defects and warning defects in various product categories. Specific issues related to product liability, such as identifying proper defendants, establishing causation and the issue of post-sale warnings. Broader policy questions about the role of litigation versus regulation in a democracy and a market economy.
Not open to students with credit in IMSE 315. (Delivered via WWW.) Introduction to the principles of ergonomics. Information processing, human output and control, workplace design and environmental conditions.
System and component reliability analyses of series, parallel and complex systems. Concepts of reliability, availability, and maintainability in design of systems. Methods of reliability testing and estimation.
Fundamentals of stochastic processes and their application in modeling production/inventory control, maintenance and manufacturing systems. Markov and semi-Markov chains, Poisson processes, renewal processes, regenerative processes and Markov decision processes.
Theory, practice and application of inventory, demand and supply planning techniques in multistage environments. Managing economies of scale, uncertainties, capacity constraints, and product availability in a supply chain. Integrated planning, supply chain coordination and technology enablers.
Nonlinear Optimization in Engineering LINKCrosslisted as MECH 888
Nonlinear optimization using gradient-based and evolutionary methods. Constrained and unconstrained nonlinear optimization, Karush-Kuhn-Tucker conditions, penalty and barrier methods. Applications to optimal design in sciences and engineering.
Admission to masters degree program and permission of major adviser
Total Quality Management Using Six Sigma Techniques LINK
Introduction to advanced topics in Engineering Management and the foundations of Total Quality Management (TQM). Costs of quality, statistical tools, initiating change, advanced topics, and TQM in practice. Using DMAIC, DFSS, and COPQ along with the other industry-accepted Six Sigma Quality Techniques.
Applications of principle and financial economics in industrial and systems engineering. Term structure of interest, capital asset pricing and other capital allocation models. Evaluation of real-options using binomial lattice, Black-Scholes and other pricing models.
Lecture and laboratory study of physiological factors affecting human performance during work. Includes evaluation and testing of physical work capacity, applied work physiology, and factors affecting work performance in stress producing environments.
Focus on the individual in the industrial working environment. Emphasis on evaluation of fatigue, training, shift work, perception, vigilance, and work-rest scheduling as they relate to the working environment.
Quality Engineering: Use of Experimental Design and Other Techniques LINK
Extension of industrial quality control methods and techniques. Off-line and online quality control methods. Development of quality at the design stage through planned experiments and analyses. Experimental design methods include factorial, 2k, 3k, and factional factorials designs. Includes applied project in design of quality.
Difference and differential equation models directly from series of observed data. Underlying system analysis including impulse response, stability and feedback interpretation. Forecasting and accuracy of forecasts. Periodic and exponential trends in seasonal series. Modeling two series simultaneously. Minimum mean squared error control and forecasting by leading indicators. Illustrative applications to real life data in science and engineering.
Philosophy, principles and methodology for discrete-event simulation modeling. Use of simulation in the planning of manufacturing and service systems. Simulation modeling perspectives and languages, variance reduction techniques, model verification and validation, and output analysis.
Current topics in major areas of study with the Department of Industrial and Management Systems Engineering that are pertinent to IMSE graduate students, in the areas of: A. Engineering Management B. Human Factors Engineering D. Manufacturing Engineering E. Operations Research