Abstract
Although the integration of machine learning into production systems has demonstrated significant potential, its real-life applications remain challenging. It is often necessary to rely on digital representations of the actual systems to design and test machine learning algorithms for controlling the systems because conducting such processes directly in real systems is expensive and risky. Hence, in this paper, we present a standardized, multi-purpose and flexible production systems simulator in Python for scientific and industrial activities, namely MLPro-MPPS, that is integrated with the MLPro package. Consequently, this allows the simulations by MLPro-MPPS to be compatible with machine learning tasks.
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