Predictive maintenance first emerged in Western developed industrial countries as a condition-based maintenance approach. It involves regular or continuous condition monitoring and fault diagnosis of a machine's critical or required parts during operation, assessing the equipment's current state, predicting future trends in its condition, and preemptively formulating predictive maintenance plans based on the equipment's condition trends and potential failure modes. This determines the optimal time, method, and scope of maintenance, as well as the necessary technical and material support. Integrating condition monitoring, fault diagnosis, fault condition prediction, maintenance decision support, and maintenance activities, predictive maintenance is an emerging equipment management and maintenance approach in smart factories. Predictive maintenance offers the potential to optimize maintenance in smart factories, maximize equipment service life, and help enterprises achieve better results with lower costs, thereby avoiding potentially significant losses. In the context of smart factories, predictive maintenance has become a growing demand for more and more enterprises.

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