Industrial Systems Design and Analysis: High-Fidelity Learning Environments for Engineering Education

Today, engineering education addresses industrial systems (factories, warehouses, and logistics systems) by focusing on engineering methods and tools used in solving associated design, planning, and control problems. The corresponding body of knowledge is very broad, but without a common, unifying theoretical base. Compounding this problem, students rarely see more than unrealistically simplified illustrations of 'real' industrial systems problems. Without a unifying theoretical foundation, and without a comprehensive exposure to the domain, students are left with a poorly integrated set of technical skills, and largely without insight into the complexities of applying those skills in practice.

This project radically reshapes the teaching of industrial systems by shifting focus from the disparate collection of engineering methods and tools to the domain in which those methods and tools find application. We are creating a new pedagogical platform that we call 'virtual industrial systems,' or VIS. A VIS is an integrated computing environment that includes a rich, complex data repository describing a particular industrial system (a case study, only much richer in detail), a set of specific computational tools for description, visualization, analysis and synthesis, and a common user interface that minimizes time to learn to use the tools in the context of the case. A VIS may incorporate simulation, interactive decision making, 2D and 3D representations, video recordings, or any other information source in digital form. This project is developing at least one complete implementation of a VIS.

As envisioned, a VIS is a platform not just for learning about industrial systems, but also for learning the basics of specific methods, such as statistics, optimization, and economic analysis. Using a VIS, a student may practice specific engineering methods and tools, but also may explore a wide range of 'what happens if?' questions. We believe that access to a VIS dramatically improves motivation, content mastery, and context-specific insight.