The study presents a decision support model for optimizing aircraft maintenance plans, targeting repairable units with hidden functions. The model addresses the complexities of integrating multiple factors, such as aging, the availability of hidden functions during operation, the varying effectiveness of restoration and repair tasks, and the operational and economic consequences of failure.It considers a combination of inspections, restorations, and a discard task at the unit’s predefined renewal age, for the “non-safety effect” failure category. It incorporates the Kijima type II model to account for the effect of imperfect restoration and the concept of mean fractional dead time to identify the optimal intervals for inspections, the number of inspections needed within each restoration cycle, and the frequency of restorations in a renewal cycle. Real-world adapted numerical examples are used to demonstrate the model’s application. Sensitivity analysis further enhances the model’s utility by determining the influence of reliability and cost parameters on maintenance optimization outcomes. The results show that, in the absence of aging, restoration effectiveness has a profound effect on the total cost and optimal set of solutions. With as-bad-as-old restoration effectiveness, the optimal alternative involves maximizing the number of inspections without resorting to restoration. Conversely, with as-good-as-new restoration effectiveness, the optimal alternative should harmonize a moderate number of inspections with a moderate number of restorations. Additionally, the influence of the costs associated with restoration and accidents suggests that frequent inspections at smaller intervals are essential to mitigate the risk of failure. Maintenance managers can utilize the proposed model as a practical tool to optimize maintenance by comparing and selecting strategies based on effectiveness and cost parameters, thereby enhancing the reliability of repairable systems with hidden failures.