Predictive maintenance using digital twins: A systematic literature review
Theological University of Apeldoorn · Wageningen University & Research · +1 more institution
Abstract
Predictive maintenance is a technique for creating a more sustainable, safe, and profitable industry. One of the key challenges for creating predictive maintenance systems is the lack of failure data, as the machine is frequently repaired before failure. Digital Twins provide a real-time representation of the physical machine and generate data, such as asset degradation, which the predictive maintenance algorithm can use. Since 2018, scientific literature on the utilization of Digital Twins for predictive maintenance has accelerated, indicating the need for a thorough review. This research aims to gather and synthesize the studies that focus on predictive maintenance using Digital Twins to pave the way for…
Citation impact
- FWCI
- 52.56
- Percentile
- 100%
- References
- 122
Authors
3Topics & keywords
- Predictive maintenance
- Computer science
- Key (lock)
- Data science
- Abstraction
- Corrective maintenance
- Machine learning
- Engineering
- Industry, innovation and infrastructure