Effective strategies for Prognostics and Health Management (PHM) are fundamental to advancing the operational integrity and economic sustainability of complex industrial assets. Overcoming the persistent hurdle of modeling the intricate temporal nonlinearities and stochastic behaviors inherent in degradation processes is central to this endeavor. This study introduces an optimized maintenance framework based on real-time condition monitoring for systems subject to stochastic wear, utilizing an innovative nonlinear Wiener process model with time-scale transformation. By framing the optimization objective as the minimization of the long-term average cost rate, we derive explicit expressions for the optimal inspection interval and the threshold for preventive maintenance. A likelihood ratio test demonstrates the superiority of the nonlinear model over linear alternatives. A case study on a Power Take-Off (PTO) unit validates the effectiveness of the proposed method, showing its ability to balance failure risk and maintenance cost efficiently. The proposed strategy provides a practical and scientifically grounded tool for managing systems with nonlinear degradation characteristics.

The existing research on multi-component systems mostly assumes that the faults between components are independent and ignores their practical correlation, which will inevitably affect the calculation of system warranty cost and warranty availability. In order to quantitatively analyze the impact of fault independence and fault correlation between components on the minimum two-dimensional extended warranty (EW) cost-availability ratio of the system, this paper establishes a two-dimensional EW cost model and availability model for multi-component systems considering fault correlation based on incomplete periodic preventive maintenance (PM), and forms a warranty cost-availability ratio model accordingly. Subsequently, the artificial bee colony (ABC) intelligent optimization algorithm was introduced to solve the model, and a case study was conducted on the transmission system of a certain new energy vehicle. Through numerical comparison, it was found that considering fault correlation compared to the assumption of fault independence would increase the warranty cost-availability ratio of the system by 20%, providing more practical warranty references for users and manufacturers, and verifying the superiority of the model. Finally, a sensitivity analysis was conducted on the model to guide its more effective implementation and application.

Extended warranty (EW) is an optional contract that typically provides additional guarantee to users by the manufacturer after the initial warranty period of the equipment expires. To meet users' demand for minimizing the EW cost-availability ratio during the device's EW period and protect the manufacturer's profit, this article innovatively proposes a grouping preventive maintenance (GPM) strategy for multi-part series system, based on the consideration of user and manufacturer sharing warranty cost proportionally. This strategy can integrate the preventive maintenance (PM) of each individual component in the system, thereby reducing the total number of PM times and lowering the preparation cost for PM. The decision objective of the GPM strategy is to minimize the cost-availability ratio of the system's EW, and the decision variables are the PM interval and PM improvement factor. In the case analysis, taking the power system of electric vehicles as the research object, it was found that after adopting the GPM strategy, the EW cost-availability ratio of the system reduced by 16.6%, thus verifying the superiority of the GPM strategy proposed in this paper.