Stochastic optimization of aero-engine maintenance schedules

In this thesis the maintenance scheduling optimization problem of a multi-component system is formulated as a multi-objective stochastic dynamic problem, which is solved by first transforming the multi-objective formulation into a single-objective one via the weighted-sum method, and then using an iterated two-stage stochastic linear programming approach to solve the stochastic problem. The main application is the maintenance of a commercial gas turbine aero-engine. The model determines optimal opportunistic replacement schedules considering both deterministic and stochastic engine configurations. The proposed methodology provides maintenance planners with a decision tool that simultaneously minimizes the expected total cost of providing the maintenance service, and the expected total number of service interruptions due to maintenance during a finite horizon. The analysis presented in this thesis considers the indentured configuration of a modular aero-engine and investigates the sensitivity of the solutions to variations in a number of critical parameters.