Optimization of inspection and repair strategies for military gas turbine engines using a risk-based maintenance approach

Purpose Despite advancements in engine performance and reliability, the complexity of engine failures and limited failure data highlight the need for improved risk assessment and maintenance strategies. This study develops an optimization framework for the inspection and repair (I&R) scheme of military gas turbine engines using a risk-based maintenance (RBM) approach. Design/methodology/approach Using Bayesian decision theory and a probabilistic risk analysis model, the proposed framework accounts for inspection, repair, and risk costs, focusing on the J85 engine's No. 2 bearing. The parametric analysis examines the effects of bearing time change intervals (TCI) and periodic examination (PE) intervals on risk indices, operation ratios, and cost breakdowns. Findings While NRIFSD risk indices did not meet required standards, ERLOA remained within acceptable limits, and operation ratios exceeded 90%. Extending TCI and PE intervals reduced overall costs by minimizing replacements, though shorter intervals raised inspection costs. The optimal cost for the bearing TCI of 5,400 h occurred at a PE interval of 1,200 h, where frequent inspections had the most significant impact on minimizing risk. Originality/value A novel probabilistic framework for gas turbine engine inspection/repair/replacement planning. Bayesian pre-posterior analysis for inspection/repair/replacement schedules. Inspection/repair or replacement optimizations for gas turbine engines.