Spring 2013

Techniques for handling uncertainties in engineering design: discrete and continuous random variables; expectations, probability distributions and transformations of random variables; limit theorems; approximations and applications.

Sampling distributions; parameter estimation, hypothesis testing; analysis of variance; regression; nonparametric statistics.

Basic manufacturing processes including casting, machining, forming and welding; current trends in manufacturing processes including polymer, ceramic and composite material processing, and electronic device fabrication; introduction to numerical control and computer integrated manufacturing. Recommended preparation: MASC 110 or CHEM 105aL or CHEM 115aL

Facilities layout and design: material handling and transportation; site selection and sourcing; supply chain management.

Introduction to linear programming; transportation and assignment problems; dynamic programming; integer programming; nonliner programming.

Stochastic processes; Markov chains; queueing theory and queueing decision models; probabilistic inventory models. Recommended preparation: ISE 330

Examine team formation and team dynamics including organizational behavior, group dynamics, psychology, and business management, all in the context of engineering development; decision-makig and negotiation. Open only to juniors and seniors,

Concepts in modeling data for industry applications. Designing and implementing robust databases. Querying databases to extract business intelligence; Global Enterprise Resource Planning with databases.

Production planning, forecasting, scheduling, and inventory; computer integrated decision systems in analysis and control of production systems.

Business process integration is the core advantage of using ERP systems. Analyze, configure, and test business processes for a company from the ground up.

Model design to simulate discrete event systems with basic input and output analysis using high order languages, applied to industrial systems analysis and design problems.

Impact of technology on work and organizational design; effects of automation; design of improvement programs; information infrastructures; teams; individual behavioral outcomes. Upper division standing.

Utilizing principles of economic analysis for choice of engineering alternatives and engineering systems. Pre-tax and after-tax economy studies. Upper division standing.

Essentials of human factors and computer interface for the design, development, implementation, and evaluation of integrated media systems.

Individual research and readings. Not available for graduate credit.

a: Preparation and development of the senior project proposal. Not available for graduate credit. Senior standing in industrial and systems engineering.

Group work on an industrial engineering design problem in an organization. Not available for graduate credit. Senior standing in industrial and systems engineering.

Case based decision and statistical analysis. Framing engineering management situations with statistical methods. Experiments, regression, ANOVA, hypothesis, factor analysis. Open only to Fifth Year Seniors and Masterâ??s Students.

Cost control, finance, and engineering economy for construction operations.

Use of mechanical, electrical, and computer engineering, math, and computer science to design of high performance and sophisticated products and processes and systems involving mechatronic. Recommended preparation: Bachelor's degree in engineering or physical sciences, and preliminary knowledge of programming in C.

Deterministic and stochastic demand systems with static/dynamic models. Practice in inventory management, computerized procedures, materials requirements planning, just-in-time production, Kanban systems.

Advanced concepts in production planning and scheduling including resource allocation, lot sizing, flow shop and job shop scheduling, workforce scheduling and assembly line balancing. Recommended preparation: prior knowledge of operations research and probability theory.

Applying industrial and systems engineering skills to problems drawn from industry, while working in teams of 3-4 students. Teach project management skills and provide direct experience in managing and executing a group project.

Study of various aspects of integrated manufacturing and service enterprises including management, design and production functions, interfaces and related resources and information systems. Recommended preparation: manufacturing processes, probability, statistics, computer programming.

Conditions for optimality; nonlinear programming algorithms for constrained and unconstrained problems. Special problems such as quadratic, separable, fractional, geometric programming.

Planning data collection to investigate relationships between product/process design choices (materials, temperatures, etc.) and performance, empirical modeling to predict performance, identification of the best design choices. Recommended preparation: ISE 225

Principles of quality management, quality philosophies and frameworks, quality leadership and strategic planning, process management, and performance measurements.

Tree, path, flow problems, formulation and solution techniques. Methods for minimal cost flows. Applications.

Linear programming models for resource allocation; simplex and revised simplex methods; duality; sensitivity; transportation problems; selected extensions to large scale, multiobjective, and special structured models.

Simulation techniques combined with probabilistic analysis for solving problems in inventory theory, queuing theory, financial engineering, decision analysis, and other fields having a stochastic element.

Design and management of engineering teams. Group decision-making, motivation, leadership, infrastructure requirements, performance measurement, team diversity, conflict, and integration.

Principles and practices of technology development and implementation, with application to products and systems in manufacturing and services.

Explores fundamental techniques such as recursion, Fourier transform ordering, dynamic programming for efficient algorithm construction. Examples include arithmetic, algebraic, graph, pattern matching, sorting, searching algorithms.

Economic evaluations of engineering systems for both government and private industry; quantitative techniques for evaluating non-monetary consequences; formal treatment of risk and uncertainty.

Decision making under risk conditions; utility theory; sufficient statistics; conjugate prior distributions; terminal and pre-posterior analysis; Bayesian statistics versus classical statistics.

Concepts underlying the economic analysis of engineering projects; applications to call and put options; utility theory and mathematical optimizations models; and simulation. Recommended preparation ISE 220 or an equivalent course in probability.

Measurement systems for performance analysis. Determination of performance metrics, analytical models, case studies. Cross-industry comparisons, measures for manufacturing and service systems, information and knowledge workers.

Identification, formulation, and solution of financial accounting problems in engineering enterprises. Legal context of financial decisions, process cost determination and allocation, financial reports, and reporting systems. Open only to graduate students.

Reasoning under uncertainty, statistical directed and undirected graphical models, temporal modeling, inference in graphical models, parameter learning, decisions under uncertainty. Recommended preparation: An undergraduate level course in probability theory.

Concepts and methods to analyze the environmental impacts of industrial systems, including life-cycle assessment, material flow analysis, design for environment and sustainable consumption.

Decision making techniques for the engineering manager including negotiation principles, contract negotiation, dispute resolution, auctions, bidding, voting and coalition formation.

The role of enterprise resource planning systems (ERPs) in an organization and the task of implementing and managing the IS function.

Concepts of risk analysis, risk in engineered systems, environmental risk, security risks; fault trees, event trees, risk simulations; risks and decision-making. Recommended preparation: MATH 108 or MATH 116

Research leading to the master's degree; maximum units which may be applied to the degree to be determined by the department. Graded CR/NC.

Course content will be selected each semester to reflect current trends and developments in the field of industrial and systems engineering.

Current research, guest speakers in the field; review papers; guidance in preparing research proposals and special projects. Duplicates credit in the former ISE-650abc. Open only to Fifth Year Seniors and Masterâ??s Students.

Fundamental techniques for design and analysis of algorithms. Topics include: dynamic programming; network flows; theory of NP-completeness; linear programming; approximation, randomized, and online algorithms; basic cryptography. Recommended preparation: familiarity with algorithms and discrete mathematics.

Research leading to the doctorate. Maximum units which may be applied to the degree to be determined by the department. Graded CR/NC.

Credit on acceptance of Dissertation.

Credit on acceptance of Dissertation.

Credit on acceptance of Dissertation.

Credit on acceptance of Dissertation.

Credit on acceptance of Dissertation.