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The manufacturing sector has a substantial influence on worldwide energyconsumption. Therefore, improving manufacturing system energy efficiency isbecoming increasingly important as the world strives to move toward a moreresilient and sustainable energy paradigm. Batch processes are a majorcontributor to energy consumption in manufacturing systems. In batchmanufacturing, a number of parts are grouped together before starting a batchprocess. To improve the scheduling and control of batch manufacturingprocesses, we propose a system-level energy-efficient Digital Twin frameworkthat considers Time-of-Use (TOU) energy pricing for runtime decision-making. Aspart of this framework, we develop a model that combines batch manufacturingprocess dynamics and TOU-based energy cost. We also provide anoptimization-based decision-making algorithm that makes batch schedulingdecisions during runtime. A simulated case study showcases the benefits of theproposed framework.

A System-Level Energy-Efficient Digital Twin Framework for Runtime Control of Batch Manufacturing Processes