摘要
Airline operators face accidental damages on their fleet of aircraft as part of operational practice.Individual occurrences are hard to predict;consequently,the approach towards repairing accidental damage is reactive in aircraft maintenance practice.However,by aggregating occurrence data and predicting future occurrence rates,it is possible to predict future long-term(strategic)demand for maintenance capacity.In this paper,a novel approach for integration of reliability modelling and inventory control is presented.Here,the concept of a base stock policy has been translated to the maintenance slot capacity problem to determine long-term cost-optimal capacity.Demand has been modelled using a superposed Non-homogeneous Poisson Process(NHPP).A case study has been performed on damage data from a fleet of Boeing 777 aircraft.The results prove the feasibility of adopting an integrated approach towards strategic capacity identification,using real-life data to predict future damage occurrence and associated maintenance slot requirements.
