Energy digital twins in smart manufacturing systems: A case study

Among core Industry 4.0 technologies, the Digital Twin represents a promising smart technology and tool that researchers are investigating to help improve energy efficiency at the shopfloor level by analyzing and optimizing energy consumption. Energy Digital Twins are a relatively new area of research, only gaining popularity in industry applications and academia recently. where a comprehensive literature review uncovered only one 'true' Energy Digital Twin application across published research to date. To address this research gap, an Energy Digital Twin for smart manufacturing systems was developed and evaluated in this study. In particular, the study focused on bidirectional parameter communication between the physical and the virtual part with the aim of optimizing the energy used in the manufacturing process. To address this research gap, the research objective is to create and evaluate an application of an energy optimizing Digital Twin for a Heating Tunnel. Following the definition of a Digital Twin, the research methodology and experimental setup have three major components: i) the Heating Tunnel as the physical object, ii) the digital counterpart constructed using Python to house the digital control logic and linear energy optimization feedback model, and iii) the connecting fabric, in form of a bidirectional OPC UA communication protocol. The optimization model ingests input parameters of setpoint temperature, power level, and targeted overshoot time, and after running the simulation, returns a calculated value of the required turn off temperature to the real-time heating process of the physical system. Results show that the Energy Digital Twin is effective at maintaining the maximum temperature range of the Heating Tunnel during the heating process, in addition to reducing the energy consumption and cost for all trial runs compared to the original process. Overall, the study successfully created and evaluated a functioning energy optimizing Digital Twin with bidirectional, automated feedback. The results of this research emphasize the potential impact of Energy Digital Twin applications in any manufacturing process and show the promise of future work in this realm of Energy Digital Twins.