A multi-objective approach for solving a replacement policy problem for equipment subject to imperfect repairs

• Published in: Applied Mathematical Modelling Vol. 86; pp. 1 - 19
• Main Authors: Azevedo, Rafael Valença, Moura, Márcio das Chagas, Lins, Isis Didier, Droguett, Enrique López
• Format: Journal Article
• Language: English
• Published: New York Elsevier Inc 01.10.2020; Elsevier BV
• Subjects: Computer simulation; Decision analysis; Decision making; Discrete Event Simulation; Discrete event systems; Failure; Generalized Renewal Processes; Genetic algorithms; Impact analysis; Imperfect Repair; Maintenance costs; MOGA; Replacement Policy; Spare Parts; MOGA; Generalized Renewal Processes; Discrete Event Simulation; Spare Parts; Imperfect Repair; Replacement Policy
• ISSN: 0307-904X; 1088-8691; 1872-8480; 0307-904X
• DOI: 10.1016/j.apm.2020.04.007

•Novel multiobjective model to replacement policy decisions.•Imperfect repair and multiobjective approach in unique replacement policy decision model.•Availability of spare parts affects reliability and cost performances of the policy.•Genetic algorithm coupled with event simulation is a powerful tool to maintenance optimization. This paper proposes a multi-objective approach to model a replacement policy problem applicable to equipment with a predetermined period of use (a planning horizon), which may undergo critical and non-critical failures. Corrective replacements and imperfect repairs are taken to restore the system to operation respectively when critical and non-critical failures occur. Generalized Renewal Process (GRP) is used to model imperfect repairs. The proposed model supports decisions on preventive replacement intervals and the number of spare parts purchased at the beginning of the planning horizon. A Multi-Objective Genetic Algorithm (MOGA) coupled with discrete event simulation (DES) is proposed to provide a set of solutions (Pareto-optimum set) committed to the different objectives of a maintenance manager in the face of a replacement policy problem, that is, maintenance cost, rate of occurrence of failures, unavailability, and investment on spare parts. The proposed MOGA is validated by an application example against the results obtained via the exhaustive approach. Moreover, examples are presented to evaluate the behavior of objective functions on Pareto set (trade-off analysis) and the impact of the repair effectiveness on the decision making.