PROBABILISTIC ENGINE MAINTENANCE MODELING FOR VARYING ENVIRONMENTAL AND OPERATING CONDITIONS

The maintenance and reliability of aircraft engines is strongly influenced by the environmental and operating conditions they are subjected to in service. A probabilistic tool has been developed to predict shop visit arisings and respective maintenance workscope that depends on these factors. The tool contains a performance model of the engine and a number of physics-based damage mechanisms (at piece part level). The performance model includes variation of performance relevant parameters due to production scatter and delivers the conditions to determine the deterioration of the individual parts. Shop visit maintenance is modeled as a result of limitations to engine operation, e.g. reaching TGT limit, or mechanical deterioration. The influence of maintenance actions on engine performance is determined on component basis. The maintenance strategy can consist of proactive and reactive maintenance elements. The decision of repair or replacement of any single part is implemented through a sum of different logic rules in the model. The loading capacity scatter depends on the engine type and is operator independent. It is represented via data-driven distribution functions, in which the probabilities of failure, repair and replacement for each part are specified depending on the number of reference flight cycles. The loading variation is considered through a physics-based cycle weighting. The developed tool runs a Monte Carlo simulation in which a fleet of engines is modeled through their respective lifetime of maintenance and performance deterioration. Using an example it is shown that the model can describe the effects of varying environmental and operating conditions on part damage, and therefore engine maintenance cost and reliability.