A New Inspection Heuristic for a Condition-Based Maintenance Policy in a Spare Part Returns Context

In this paper we propose a new heuristic based approach to determine the optimal non-periodic inspection plan on a finite time horizon for a condition-based maintenance. The considered system consists of a single machine subject to a continuous, monotonous and stochastic degradation which can lead to failure and consequently to a maintenance action. The maintenance actions consist of replacing the main part of the production unit by another spare part. Spare parts are classified by their degradation into several qualities: New spare parts, which are provided by external supplier with a fixed delivery time. Used spare parts which are collected and provided by the maintenance service with fixed remanufacturing time, Depending on decision thresholds, the replacement might be either preventive or corrective. The objective is to determine the order/remanufacturing decision threshold (from which an order/remanufacturing is to be launched) and the preventive maintenance decision threshold to perform the preventive replacement. Our approach aims to minimize the total cost due to replacement, storage, inspection, order/remanufacturing costs and downtime penalty. A simulation-based genetic algorithm is proposed. At the end numerical examples are given to observe the performance of the proposed heuristic.