Enhancing maintenance management of critical equipment using digital twin

Digital twin (DT) technology develops virtual models of objects digitally, simulating their behavior in the real world based on data. Recent advances in DT have greatly facilitated the development of predictive maintenance for critical equipment, enabling accurate identification of equipment conditions, proactive prediction of faults, and enhanced reliability. This research aims to explore the previous studies on DT for proactive maintenance applications of critical equipment. The literature review shows the importance of DT in maintenance management for improving equipment RAMS (reliability, availability, maintainability, and safety). Finally, the findings of this study will be valuable to professionals who desire and aspire to implement DT to achieve maintenance excellence.