An improved imperfect maintenance strategy for multiperiod randomly failing equipment with stochastic repair times. Issue 2 (15th March 2021)

• Record Type: Journal Article
• Authors: Dellagi, Sofiene; Darghouth, Mohamed Noomane
• Is Part Of: Journal of quality in maintenance engineering. Volume 28:Issue 2(2022)
• Page Start: 491
• Page End: 505
• Publication Date: 2021-03-15
• Subjects: Cost model -- Preventive maintenance -- Imperfect repair -- Multi-period systems -- Stochastic repair times; Plant maintenance -- Quality control -- Periodicals; Total quality management -- Periodicals; Total productive maintenance -- Periodicals; 658.202
• DOI: 10.1108/JQME-10-2020-0105
• Languages: English
• ISSNs: 1355-2511

Abstract

Abstract : Purpose: In this paper, a maintenance strategy based on improved imperfect maintenance actions with stochastic repair times for multiperiod randomly failing equipment is developed. The main objective is to minimize the total maintenance cost by jointly finding the optimal preventive maintenance (PM) cycle and planning horizon. Design/methodology/approach: A model based on the mathematical theory of reliability is developed to minimize the total maintenance cost by jointly finding the optimal couple: PM cycle T * and planning horizon H *. The proposed model aims to characterize the evolutionary impact of imperfect PM actions on the equipment failure rate and the resulting mean number of failures. The conventional threshold accepting (TA) algorithm is implemented to solve the proposed model. A numerical example for a given set of input parameters is presented in order to show the usefulness of the proposed model. A sensitivity analysis of some of the key parameters is performed to demonstrate the coherence of the developed maintenance policy. Findings: The obtained results showed a sensitive trade-off between PM frequency and the total maintenance cost. Performing PM actions more frequently helps significantly to reduce the expected number of corrective maintenance actions and the corresponding total cost. It has also been found that improving the efficiency of the PM actions allows for maintaining the equipment less frequently by increasing the time between successive PM actions. Research limitations/implications: Given the complexity of the objective function to be minimized and the stochastic nature of the model's parameters, the authors limited this study to equally cyclic production periods over the planning horizon. Practical implications: The present model aims to provide an integrated maintenance/production comprehensive framework to assist planners in establishing maintenance schedules considering multiperiod randomly failing production systems and the evolutionary impact of imperfect PM actions on the equipment failure rate. Originality/value: Contrary to the majority of existing works in the literature dealing with maintenance strategies, the authors consider that repair times are stochastic to provide a more realistic framework. In addition, the developed model considers the impact of imperfect maintenance on the equipment's mean time to failure. Thus, the evolutionary impact of imperfect PM actions on the equipment failure rate and the resulting mean number of failures is characterized. Simultaneously, the production planning horizon along with the length of each PM cycle is optimized in order to minimize the total maintenance cost over the planning horizon.