A Case Study for Enhancing Maintenance of Cyber-Physical Systems With Digital Twin

Cyber-physical system (CPS) serves as integral critical components across various domains, including autonomous vehicles, where reliability and safety are paramount. Maintenance of such systems poses unique challenges due to their complex interplay between physical and digital objectives. Digital twin technology offers a significant advancement in maintenance by creating virtual representations of physical assets. This paper outlines a standardized process for employing digital twins in CPS maintenance, illustrated through a case study. We discuss the implementation of digital twins in the context of CPS maintenance and elucidate their role in improving fault detection, diagnosis, and condition-based maintenance strategies. The case study demonstrates the effectiveness of digital twins in reducing downtime, decreasing failure consequences, optimizing maintenance schedules, and enhancing overall system reliability. Our findings underscore the significance of digital twins in revolutionizing maintenance practices for CPS, paving the way for safer and more efficient operation of autonomous vehicles and similar CPSs.