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Deogratias Kibira, Guodong Shao, Rishabh Venketesh, Matthew Triebe
Developing digital twins for manufacturing applications is challenging due to insufficient modeling frameworks and standardized procedures. As a result, the
The applications of digital twins continue to grow with the volume and variety of data collected. These data support the modeling of function, behavior, and
Robots are increasingly being adopted in manufacturing industries and this trend is projected to continue. However, robots like all equipment, degrade once in
Developing a digital twin (DT) involves establishing (1) a predictive capability (a model) relevant to the application, (2) means to collect data from the
Building a digital twin of a manufacturing system can positively impact its performance with respect to productivity, energy consumption, product quality, and