Joint optimization of preventive maintenance and spare parts logistics for multi-echelon geographically dispersed systems

Abstract

Preventive maintenance scheduling and optimization of logistic operations in geographically dispersed systems is an intricate decision-making problem, as maintenance activities have close interactions with spare parts logistics. Planning of spare parts logistics aims to get the right spare parts to the right places at right times for the necessary maintenance activities to take place, while keeping minimal requirements on maintenance resources and maintaining high utilization of assets. This paper considers such a problem by concurrently pursuing preventive maintenance scheduling and spare parts inventory planning problem for a set of geographically dispersed assets, each consisting of multiple degrading components. This paper also shows that the assumption of a multi-echelon maintenance network brings opportunities to improve the system performance through sharing inventories between maintenance facilities. Technically, the decision-making problem is modelled as a stochastic optimization problem and a novel simulation-based metaheuristic is proposed to solve it to obtain the integrated decision-making policy. Through numerical examples, the proposed integrated policy is shown to effectively reduce the operating cost by capturing the trade-offs between asset utilization, maintenance costs and consumption of maintenance resources.