Digital-Twins-Driven Semi-Physical Simulation for Testing and Evaluation of Industrial Software in a Smart Manufacturing System

• Published in: Machines (Basel) Vol. 10; no. 5; p. 388
• Main Authors: Cheng, Keqiang, Wang, Qiang, Yang, Dongyu, Dai, Qingyun, Wang, Meilin
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-05-2022
• Subjects: accelerated testing; Accelerated tests; Aging; Aircraft; Automation; digital twin; Digital twins; fault injection; industrial software; Manufacturing; Physical simulation; Preventive maintenance; Process controls; Robustness; semi-physical simulation; Simulation; Software; Software quality; Software reliability; Steel production; Stepping motors
• ISSN: 2075-1702; 2075-1702
• DOI: 10.3390/machines10050388

To satisfy the needs of the individualized manufacturing of products, the smart manufacturing system (SMS) is frequently reconfigured. To quickly verify the reliability and adaptability of industrial software in reconfiguring the SMS for new or upgraded product orders, a semi-physical simulation method for testing and evaluation of industrial software is proposed based on digital-twins-driven technology. By establishing a semi-physical simulation model of SMS, the reliability and robustness of the software system are quickly verified by running industrial software in various manufacturing scenarios. In this paper, the key technologies to carry out semi-physical simulation testing and evaluation of industrial software for SMSs are expounded in detail, including how to synchronize cyber and physical systems, how to conduct semi-physical accelerated simulation testing, and how to identify defects quickly in industrial software used in actual production environments. By establishing a semi-physical simulation production line model for stepper motors, the effectiveness and practicality of the proposed approach are verified, and the testing verification time of industrial software is significantly reduced. Finally, the robustness of the industrial software for SMS is further verified by conducting fault injection testing, so as to provide implications for fault prognostics or fault-prevention research.