Abstract: To develop a fully complete set of errors associated with modeling and simulation, it is necessary to express every error that could impact the accuracy of a computational model's prediction of the real world system (i.e., ...

Abstract: To develop a fully complete set of errors associated with modeling and simulation, it is necessary to express every error that could impact the accuracy of a computational model's prediction of the real world system (i.e., ...

Abstract: We present a framework for establishing credibility of a machine learning (ML) model used to predict a key process control variable setting to maximize product quality in a component manufacturing application. Our model ...