Industrial Engineering (IE)

Measurement and analysis of work systems. Ergonomics and the environmental, physical, psychological aspects of work. Work measurement techniques including time study, pre-determined time systems and work sampling. Classroom and laboratory experiences are utilized in instruction.

Emphasis is on formulating and solving real-world deterministic optimization problems. Sensitivity of the solutions to variations in parameter values is addressed.

Introduction to statistical quality control methods and systems for analyzing and controlling product quality in industrial and business settings. Design of inspection plans for quality characteristics. Statistical process control charts and acceptance sampling. Introduction to reliability.

Ergonomics focuses on human capabilities and the interfaces between individuals and their environment. Concepts from signal detection theory, anatomy, physiology and controls are presented and then used to solve design problems in a wide variety of applications. Two lectures and one lab per week.

Addresses those activities in an organization that are directly related to producing goods or providing services. Planning, execution, and control of functions are examined. The focus is on organizational processes in which people, capital, and material (inputs) are combined to produce services and goods (outputs). Such processes may be found in banks, factories, stores, hospitals, etc. Subjects include forecasting, capacity planning, operations design, scheduling, and project management.

An introduction to building and analyzing models using simulation techniques. Focus is on developing models and gathering meaningful performance data for analysis and decision making in engineering design. Concepts of verification and validation are addressed.

Introduction to the process of engineering design. Application of this process to designing a hardware and software solution to a physical problem faced by an autonomous robotic vehicle.

The systems integration process includes planning, design, implementation and control. Student projects apply this process to industrial engineering functional areas.

Emphasis on probabilistic models: decision theory and games, scheduling, inventory, queuing, and Markov Chains. Solutions to real-world problems developed using hand computations and computer software.

Special advanced topics in Industrial Engineering may include Advanced Manufacturing, Lean Manufacturing, Six Sigma, Engineering Management, Advanced Quality Control, etc.

Students work in teams on a significant project involving design or re-design of an operational product, process, or procedure in either an industrial or a service setting. As a minimum, students will consider objectives and criteria, resources, interface with other functional areas, constraints, alternatives, and operational specifications. The student will prepare a written report, and a professional presentation written will be made to the host company.