Industrial and Systems Engineering

Computer programming and the use of computers to solve engineering and mathematical problems. Emphasis will be placed on applying problem solving skills. This intensive course is specifically directed towards those students who are pursuing technical careers in fields employing a reasonably high degree of mathematics. The programming language used will depend on the demands of the departments in the college. In one semester, several languages may be taught, no more than one per section. If you are required to learn a specific language, be sure to enroll in the correct section. GR-M†

Optional laboratory course in conjunction with CGS 2425. Required for ISE majors. GR-M†

An introduction to and overview of the profession, including career planning, professionalism and communication, ethics, teamwork, industry site visits, industrial speakers, and selected solution methods for problems in coordination and planning.

The analysis, design and maintenance of work methods. Study of time standards and work sampling. Equipment and workspace design and its impact on human performance.

Philosophy of continuous improvement and methodology for applying team problem solving to manufacturing and service industries. Hands-on application of the basic statistical quality tools; introduction to quality function deployment; concurrent engineering; business process reengineering; process analysis; benchmarking. Team project.

Design, analysis, and evaluation of man-machine systems. Emphasis on interaction of human and nonhuman components and resultant effect upon total system performance. Discussion of man’s physical, mental and psychological characteristics and limitations. (P)

Introduction to energy conservation. Supply-demand data, energy economics, investment analysis and energy legislation. Audits, waste heat recovery, cogeneration and computerized energy management systems.

Analysis of production and inventory systems. Deterministic and stochastic inventory models for single and multi-item systems. Analysis of logistics and distribution systems. Forecasting, scheduling, sequencing.

Integration of industrial and systems engineering methodologies with emphasis on methods of successful implementation. A project and case-study oriented course.

Basic principles and applications of economic decision-making between alternatives encountered in engineering systems projects. The analysis will include methodologies of economics and finance in addition to engineering fundamentals.

Study of decisions under risk and uncertainty, emphasizing utility theory, Bayesian decision theory and game theory.

Principles and methods for analyzing and designing plant facilities. Selected topics include systematic and computerized layout planning, warehouse design, materials handling and automated storage retrieval systems.

Problems and systems studies associated with honors programs representing undergraduate research. Selected advanced topics including new developments and techniques in industrial and systems engineering.

An introduction to and overview of the profession, including career planning, professionalism and communication, ethics, teamwork, industry site visits, industrial speakers, and selected solution methods for problems in coordination and planning.

The first part of a two-course sequence in which multidisciplinary teams of engineering and business students partner with industry sponsors to design and build authentic products and processes—on time and within budget. Working closely with industry liaison engineers and a faculty coach, students gain practical experience in teamwork and communication, problem solving and engineering design, and develop leadership, management and people skills.

The second part of EIN 4912-4913 sequence.

Lectures and discussions on general and specific engineering problems. Individual investigations and research reports on assigned topics. Orientation for an industrial career.

Current topics in manufacturing: automation, robotics, computer vision communication networks, labor relations, manufacturing processes. May be repeated for additional credit.

One term of industrial employment, including extra work according to a preapproved outline. Practical engineering work under industrial supervision as set forth in the College of Engineering regulations.

Use of embedded controllers in industrial control applications. An overview of computer architecture and assembly programming techniques. Interfacing microcontrollers and computers. Networking and telecommunications. Discussion of the popular communication protocols and standards and contemporary computer technologies.

Factors affecting variation in product quality. The use of control charts to evaluate and control manufacturing processes. Techniques for acceptance and reliability testing. Laboratory exercises illustrate the operation and control of manufacturing processes.

Stochastic processes as models for system behavior. Renewal theory; reliability function and hazard function. Typical failure distributions; redundant systems, models of repair and maintenance.

Introduction to the use of linear decision models, particularly linear programming and related decision-analysis optimization software, to aid in the analysis and solution of complex, large-scale decision problems. Consideration of related network modeling concepts.

Dynamic programming and optimization. Markov processes and queuing theory. Network analysis. Applications.

Applications of decision support systems in industrial and systems engineering; developing and implementing decision support systems arising in industrial and systems engineering using popular database management and spreadsheet software.

Introduction to the Internet and E-commerce; Internet tools and technologies necessary for the development of web-based decision support systems; Designing and implementing web-based decision support systems arising in the practice of industrial and systems engineering using popular software packages.

Simulation methodology and languages (such as GPSS, General Purpose Simulation System). Design and analysis of simulation experiments. Applications to the solution of industrial and service system problems.

Theory and application of vector, matrix and other numerical methods to systems problems. Simultaneous linear equations, characteristic values, quadratic forms, error analysis, use of series, curve fitting, nonlinear equations, discrete methods. The laboratory sessions will emphasize numerical solutions using MATLAB.

Practical engineering work under industrial supervision, as set forth in the College of Engineering Regulations.