An optimal sequential preventive maintenance policy under stochastic maintenance quality

This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae, and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand, or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material. This paper presents a sequential imperfect preventive maintenance policy for a degradation system. Two kinds of activity, called continuous preventive maintenance (PM) and minimal repair, are simultaneously considered when arranging discrete imperfect preventive maintenance schedules. In order to obtain the maximum benefit in a finite lifetime, an expected benefit model is formulated based on maximal/equal cumulative-hazard rate constraints, and the optimal PM intervals are obtained using a genetic algorithm (GA). It is usually difficult to determine fixed maintenance quality after performing maintenance activities. This problem is addressed in the present paper by assuming that the reduction factor is a stochastic variable following probability distributions at fixed times. It is more rational to describe the fluctuation and trend of quality of discrete preventive maintenance during a lifetime; this makes optimisation results more robust and insensitive to the randomness of the crucial parameters in imperfect PM models. A numerical case is presented to illustrate the proposed model and some discussions are summarised. 1. Introduction Many of today's system have become increasingly complicated. The importance of ensuring systems operate properly requires a level of reliability capable of avoiding failure, reducing costly breakdown and ensuring security. Preventive maintenance (PM) is necessary to restore/keep a repairable system functional. For this reason, research on optimal preventive maintenance policies is a hot issue, and one that is very important for academic research and industrial application. PM seeks to provide maximum system reliability and safety with a minimum of maintenance resources (cost, time, staff, etc.). How to assess the quality/effect of preventive maintenance and how to arrange its activities to meet one's satisfaction have been studied in practice since the 1960s. Researchers generally focus on the feasibility and cost of maintaining a repairable system. A huge …