What is the role of the digital twin concept in predictive maintenance for industrial machinery?

The digital twin concept underpins predictive maintenance by providing virtual replicas of physical machinery that simulate behavior, predict anomalies, and optimize performance. A model by Kerkeni et al. enabled continuous monitoring and early fault detection for industrial machinery, helping prevent failures and reduce downtime.

In the IIoT-based predictive maintenance framework described in the source, the digital twin is presented as a key enabler. It acts as a virtual replica of a physical system, allowing the system to simulate real-world behavior, forecast potential anomalies, and optimize operational performance. In the context of industrial machinery, a digital twin developed by Kerkeni et al. was specifically tailored to support continuous monitoring and early fault detection, which directly supports the maintenance strategy of identifying issues before actual failures occur. This role contributes to lowering downtime and optimizing energy use, aligning with the broader goals of sustainable industrial operations.