Digital twin-based real-time energy optimization method for production line considering fault disturbances

In recent years, industrial enterprises are pursuing energy reduction to meet future needs for sustainable globalization and government legislations for green manufacturing. Most existing energy optimization methods for production lines are developed based on system modeling simulation. Thus they cannot reflect the behavior and the performance of the production line in a physical shop floor in real time. In this paper, based on digital twin technologies, a digital twin-based real-time energy optimization (DT-REO) method for energy consumption reducing in production lines is proposed. This method firstly constructs a digital twin-based real-time simulation method integrating geometry, physics, production behavior, simulation rules, and data interaction. Then, by further combining energy consumption characteristics, unit production time, production state and behaviors of each production equipment, a real-time energy optimization model considering fault disturbances based on digital twin is constructed. Meanwhile, an effective solving algorithm of energy consumption control based on genetic algorithm is designed. Finally, with the practical implementation in a shell production line, the results show that this DT-REO method has practical value and guiding significance to improve the efficiency of production lines.