A Simulation‐Based Selective Maintenance Framework for Mission‐Oriented Equipment Systems Using Real‐Time Condition Mapping

Selective maintenance for mission‐oriented equipment systems is often simulated from fixed lifetime distributions or static initial ages, which can obscure component‐specific degradation before a mission. This paper proposes a simulation‐based selective maintenance framework that incorporates real‐time condition mapping into mission reliability evaluation. Multi‐domain monitoring features are reduced by kernel principal component analysis and used as health covariates in a Weibull proportional hazards model (PHM) to estimate component‐level equivalent ages. These equivalent ages initialize an event‐driven Monte Carlo mission simulation, in which pre‐mission preventive maintenance levels are selected under cost and downtime constraints and in‐mission failures trigger corrective responses. The objective is to maximize mission success probability defined by system functionality, terminal equipment state, and mission‐time tolerance. A navigation mission case study demonstrates how condition‐derived equivalent ages alter component reliability initialization and maintenance priorities under the same resource constraints. The framework links condition monitoring data, reliability modelling, and simulation‐based maintenance planning in a transparent decision process for mission‐oriented equipment systems.