A multi-distribution-based optimization method for the condition-based maintenance interval of engine components

A multi-distribution model fusion approach is proposed to address the balance among multiple failure modes, safety levels, and economic constraints in aircraft engine components. This study introduces an opportunistic maintenance interval optimization method based on the integration of multiple distribution models. By applying differentiated distribution modeling techniques, such as Weibull distribution and exponential distribution, to the various safety levels and failure modes of components, and incorporating this with a maintenance task decision framework developed through Failure Modes and Effects Analysis (FMEA), it becomes possible to systematically identify which components are suitable for opportunistic maintenance and to determine appropriate maintenance interval strategies. Reliability-Centered Maintenance Analysis (RCMA) is first utilized to evaluate the applicability of opportunistic maintenance and to define the types of latent failures that can be identified. Based on the safety and economic consequences of both concealed and evident failures, a multi-objective optimization model is then constructed to achieve a comprehensive balance between safety assurance and cost efficiency. Validation using a practical case involving an engine accessory drive unit demonstrates that the proposed method can significantly reduce unnecessary downtime and maintenance costs, while simultaneously improving the availability of critical components and enhancing overall maintenance efficiency. These outcomes are achieved without compromising stringent safety standards. This method offers a scientifically supported decision-making framework for equipment health management scenarios involving multiple failure distributions and collective maintenance requirements.