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Traditional manufacturing systems face a major transition challenge toward intelligent and sustainable manufacturing systems. Energy-efficient manufacturing has become one of the main focuses of this transition because of the high and critical consumption of energy for the production of many industrial sectors. To this aim, modeling Energy Consumption (EC) behavior is a primary step to monitor and reduce consumption. However, it requires a deep understanding of the system’s kinematic and dynamic behaviors. Hence, creating a model from scratch can be challenging, which may result in a model that does not correctly represent the real system. With the advancement of digital technologies, it is now possible to collect and analyze data from manufacturing systems in real-time. This opens the door to the possibility of modeling the energy consumption behavior of different machine states based on a data-driven …