A literature review and future perspectives on maintenance optimization

Purpose The purpose of this paper is to review the literature on maintenance optimization models and associated case studies. For these optimization models critical observations are made. Design/methodology/approach The paper systematically classifies the published literature using different techniques, and also identifies the possible gaps. Findings The paper outlines important techniques used in various maintenance optimization models including the analytical hierarchy process, the Bayesian approach, the Galbraith information processing model and genetic algorithms. There is an emerging trend towards uses of simulation for maintenance optimization which has changed the maintenance view. Practical implications A limited literature is available on the classification of maintenance optimization models and on its associated case studies. The paper classifies the literature on maintenance optimization models on different optimization techniques and based on emerging trends it outlines the directions for future research in the area of maintenance optimization. Originality/value The paper provides many references and case studies on maintenance optimization models and techniques. It gives useful references for maintenance management professionals and researchers working on maintenance optimization.