A time-series probabilistic preventive maintenance strategy based on multi-class equipment condition indicators

Feng Liu ◽  
Hao Sun ◽  
Rui Peng
Yukun Wang ◽  
Yiliu Liu ◽  
Aibo Zhang

Customer satisfaction with a purchased product is closely related to the product performance within the warranty region and even the performance during the remainder of its useful life. Every satisfied customer may boost the future sales of the same product with positive evaluations and recommendations to others, and thus will create more profits for the manufacturer. During the useful life of the product, the expected cost to the manufacturer normally depends on the warranty policy, product reliability and specific servicing strategies implemented. In this article, considering the effect of customer satisfaction on the manufacturer’s incurred cost, we investigate a periodic and imperfect preventive maintenance strategy for repairable products sold with a two-dimensional warranty policy. The customer satisfaction is measured with the probability of the customer making a repeat purchase from the same manufacturer. In the proposed model, the number of preventive maintenance actions and corresponding maintenance level are jointly derived with the objective of minimizing the expected total cost per product to the manufacturer. The performance of the proposed preventive maintenance strategy is compared with that of minimal repair corrective maintenance strategy in a numerical example, so as to illustrate its applicability. In addition, some practical implications from a detailed sensitivity analysis are elaborated.

2020 ◽  
deqiang he ◽  
Xiaozhen Zhang ◽  
Yanjun Chen ◽  
Jian Miao ◽  
Congbo Li ◽  

Abstract In view of the problems of over-maintenance and under-maintenance in the current urban rail transit maintenance strategy and the reliability of single processing of fault data, which is often inconsistent with the actual situation, an incomplete preventive maintenance strategy based on the competitive Weibull model is proposed in this paper. To make the fault mechanism processing method for urban rail vehicles more accurate, fault feature attributes and fault information sequences are introduced to classify fault data. Fuzzy cluster analysis of vehicle fault data can be performed using the formula of the competitive Weibull model, and parameter estimation of the reliability model can be performed by combining it with the graph parameter estimation method. In addition, the fault rate increase factor and service age reduction factor are introduced into the maintenance strategy, and the optimal preventive maintenance cycle and maintenance times are obtained by combining maintenance and replacement according to reliability. A quantum-genetic intelligent algorithm is used to optimize the model-solving process. Finally, the maintenance of urban rail transit train doors is taken as an example. The results of this study show that compared with the traditional maintenance strategy, the reliability of the proposed maintenance strategy is closer to the actual situation. At the same time, the proposed maintenance strategy can effectively reduce the number of parked vehicles, reduce maintenance costs, and ensure the safety of train operation, maintenance economy and performance of tasks.

Xiaolei Zhang ◽  
Chun Su

Facing the uncertainty in transaction of two-dimensional extended warranty, a flexible pricing model is presented considering imperfect preventive maintenance combined with the degradation characteristics of item. The measure of two-dimensional preventive maintenance is carried out based on specified age interval or usage interval, the effect of imperfect preventive maintenance is described by age reduction model. The extended warranty cost is modeled from the perspective of manufacturer and customer, the method of gridding search is employed to optimize the maintenance strategy under different cases. Moreover, customized extended warranty price and warranty services are proposed on the basis of consumer usage rates. The results demonstrate that it is helpful to maximize the benefit of vendor by providing customized warranty strategy, the implementation of preventive maintenance during the whole warranty period can effectively reduce warranty cost for both sides.

Xinlong Li ◽  
Yan Ran ◽  
Genbao Zhang

Preventive maintenance is an important means to extend equipment life and improve equipment reliability. Traditional preventive maintenance decision-making is often based on components or the entire system, the granularity is too large and the decision-making is not accurate enough. The meta-action unit is more refined than the component or system, so the maintenance decision-making based on the meta-action unit is more accurate. Therefore, this paper takes the meta-action unit as the research carrier, considers the imperfect preventive maintenance, based on the hybrid hazard rate model, established the imperfect preventive maintenance optimization model of the meta-action unit, and the optimization solution algorithm was given for the maintenance strategy. Finally, through numerical analysis, the validity of the model is verified, and the influence of different maintenance costs on the optimal maintenance strategy and optimal maintenance cost rate is analyzed.

2020 ◽  
Vol 28 (1) ◽  
pp. 72-84 ◽  
Sofiene Dellagi ◽  
Wajdi Trabelsi ◽  
Zied Hajej ◽  
Nidhal Rezg

This study develops an analytical model in order to determine an optimal integrated maintenance plan and spare parts management. We consider a manufacturing system, producing only one type of product, over a finite planning horizon H equal to the sum of all production periods and the production quantity of each period is known. This system is subject to a continuously increasing degradation rate. That is why a preventive maintenance strategy is adopted in order to face the increasing failure rate. We noted that contrarily to the majority of studies in literature, we take into account the impact of the production rate variation on the manufacturing system degradation and consequently on the adopted optimal maintenance strategy. In addition, the real need of spare parts relative to the scheduled maintenance actions is taken into account. In fact, the purpose of our study consists at determining the optimal preventive maintenance frequency and the optimal quantity of spare parts to order by minimizing a total cost, including maintenance and spare parts management. Numerical examples are presented along with a sensitivity study in order to prove the use of the developed model for deriving the optimal integrated strategy for any instance of the problem.

Zhong-Zhe Chen ◽  
Hong-Zhong Huang ◽  
Yu Liu ◽  
Qiang Miao ◽  
Pei-Yu Ren

In this paper, reduction factor, which describes the degree of service age reduction resulting from the preventive maintenance, is introduced into a condition-based maintenance strategy. The model determining the sequential test intervals is formulated under the constraint that the probability that the failure has not test successfully within each test interval should be less than a fixed threshold. The failure risk of deteriorating system can be reduced via shortening test interval. The effectiveness of the presented methods is illustrated via a numerical case.

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2650 ◽  
Lubing Xie ◽  
Xiaoming Rui ◽  
Shuai Li ◽  
Xin Hu

Owing to the late development of offshore wind power in China, operational data and maintenance experience are relatively scarce. Due to the harsh environmental conditions, a reliability analysis based on limited sample fault data has been regarded as an effective way to investigate maintenance optimization for offshore wind farms. The chief aim of the present work is to develop an effective strategy to reduce the maintenance costs of offshore wind turbines in consideration of their accessibility. The three-parameter Weibull distribution method was applied to failure rate estimation based on limited data. Moreover, considering the impacts of weather conditions on the marine maintenance activities, the Markov method and dynamic time window were used to depict the weather conditions. The opportunistic maintenance strategy was introduced to cut down on the maintenance costs through optimization of the preventive maintenance age and opportunistic maintenance age. The simulation analysis we have performed showed that the maintenance costs of the opportunistic maintenance strategy were 10% lower than those of the preventive maintenance strategy, verifying the effectiveness of the proposed maintenance strategy.

2014 ◽  
Vol 988 ◽  
pp. 653-658
Gang Lei ◽  
Chao Deng ◽  
Bo Sheng

This paper addresses the problem of preventive maintenance optimization for NC machine tool. Firstly, the NC machine tool is divided into four subsystems according to the function module. The failure probability density function of each subsystem is estimated with the fault information records. Then, the optimal preventive maintenance period is estimated for each subsystem considering the availability. The optimal periods of all the subsystems are used to derive the preventive maintenance strategy of the whole machine. Finally, a numerical case is presented and the result shows the performance of the proposed approach.Keywords: NC machine tool, subsystem, availability, preventive maintenance

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