This course introduces students to industrial engineering and provides students with foundational tools used in the profession. The course is intended to prepare students for their first co-op experience in industrial engineering by exposing them to tools and concepts that are often encountered during early co-op assignments. The course covers specific tools and their applications, including systems design and integration. The course uses a combination of lecture and laboratory activities to cover hands-on applications and problem-solving related to topics examined in lectures.

This course aims to help undergraduate students in understanding the latest software engineering techniques and their applications in the context of industrial and systems engineering. The topics of this course include the fundamental concepts and applications of computer programming, software engineering, computational problem solving, and statistical techniques for data mining and analytics.

This course covers statistics for use in engineering as well as the primary concepts of experimental design. The first portion of the course will cover: Point estimation; hypothesis testing and confidence intervals; one- and two-sample inference. The remainder of the class will be spent on concepts of design and analysis of experiments. Lectures and assignments will incorporate real-world science and engineering examples, including studies found in the literature.

This course covers the physical and cognitive aspects of human performance to enable students to design work places, procedures, products and processes that are consistent with human capabilities and limitations. Principles of physical work and human anthropometry are studied to enable the student to systematically design work places, processes, and systems that are consistent with human capabilities and limitations. In addition, the human information processing capabilities are studied, which includes the human sensory, memory, attention and cognitive processes; display and control design principles; as well as human computer interface design.

One semester of paid work experience in industrial engineering.

This course covers the process and the analysis methods used to produce goods and services to support of the production and operations management functions. Topics include: forecasting, inventory policies and models, job shop scheduling, aggregate production planning, and ERP systems. Students will understand the importance of production control and its relationship to other functions within the organization, and the role of mathematical optimization to support production planning. The course emphasizes how a production process can be characterized by a process that requires answering a sequence of decision-making problems. The course will show how the production functions integrate with each other and how their coordination can be automated through mathematical programming. Identifying opportunities for improvement through optimization is also highlighted.

This course focuses on the role of engineering in value creation. In particular, the effective integration of engineering activities for the transformation of novel ideas and technologies into marketable products and services. Topics include value engineering and value analysis, the engineering value chain, the innovation process, engineering sustainable value, and the technology development and management process.

In conference with a faculty adviser, an independent engineering project or research problem is selected. The work may be of a theoretical and/or computational nature. A state-of-the-art literature search in the area is normally expected. A formal written thesis and an oral defense with a faculty thesis committee are required. Submission of bound copies of the thesis to the library and to the department and preparation of a written paper in a short format suitable for submission for publication in a refereed journal are also required. Approval of department head and faculty adviser needed to enroll.