SYSEN 5340 - Digital Twins of Future Systems

Spring. 3 credits. Student option grading.

Prerequisite: STSCI 2100.

M. Tayarani.

In this course students learn how to setup a mathematical simulation model to predict the system outcomes based on variable data. To be an expert in DT one need to know about data science, predictive analytics, machine learning, and artificial intelligence. Digital Twin can be thought of as a bridge between the physical and digital system. The virtual presentation of a physical system enables us to link all steps of a process including input supply, production process, performance evaluation, and customer satisfaction. DT allows us to analyze the data and monitor a system, so to head off problems before they occur. Thus, mangers will be able to consistently improve efficiency of a system by reducing its failure rates. This can open up new business opportunities.

Outcome 1: Collect and analyze data to evaluate system performance.

Outcome 2: Mathematically model systems.

Outcome 3: Design digital twins of complex systems.