Establishing a reliable mechanism model of the digital twin machining system: An adaptive evaluation network approach


Digital twin technology can build virtual replicas of physical entities to observe, analyze, and control the machining process. The virtual model always simplifies the physical entity as limited by the current technical level, so that the digital twin model cannot fully reflect the physical entity with high-fidelity, leading to a particular error rate in the prediction and decision-making. Such systematic decision-making lacks enough reliability, which could mislead decision-makers and even lead to irreparable losses. To overcome this challenge, this paper constructs an adaptive evaluation network for the digital twin machining system (DTMS), where the decision-making error on the process route is formed into the network to evaluate its reliability. Finally, the feasibility of the proposed method is verified by the reliability evaluation on the DTMS of an aerospace part’s machining process. © 2021 The Society of Manufacturing Engineers

Journal of Manufacturing Systems
Yuqian Lu
Yuqian Lu
Principle Investigator / Senior Lecturer

My research interests include smart manufacturing systems, industrial AI and robotics.