This paper proposes a new reliability modeling approach for gas turbine APU (Auxiliary Power Unit). The main objective is to develop a practical procedure that can be used to predict the number of APU failures and prioritize failure risks within a fleet. The result can be used to better arrange repair activities and optimize resource allocation. The new method is statistical based and incorporates a variable repair effectiveness factor and virtual age concept. It is intended for aftermarket APUs with the assumption that an APU fleet has been in service long enough such that sufficient data has been accumulated. Many existing reliability models and forecasting approaches have certain limitations. This study develops a quantitative approach to resolving the reliability, repair and service challenges arising from complex repairable systems like gas turbine APUs. In additional to aerospace systems, it has the potential to be adapted to other applications.
No takes yet. Share an insight, caveat, or question.
Wang et al. (2015) studied this question.
Synapse has enriched 3 closely related papers on similar clinical questions. Consider them for comparative context: