Behavior of dynamic preventive maintenance optimization for machine tools

Author(s):  
Gisela Lanza ◽  
Stephan Niggeschmidt ◽  
Patrick Werner
1998 ◽  
Vol 30 (12) ◽  
pp. 1099-1108 ◽  
Author(s):  
TADASHI DOHI ◽  
TAKASHI AOKI ◽  
NAOTO KAIO ◽  
SHUNJI OSAKI

Author(s):  
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.


Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2650 ◽  
Author(s):  
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.


2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Ruifeng Yang ◽  
Jianshe Kang ◽  
Zhenya Quan

Nuclear power plants are highly complex systems and the issues related to their safety are of primary importance. Probabilistic safety assessment is regarded as the most widespread methodology for studying the safety of nuclear power plants. As maintenance is one of the most important factors for affecting the reliability and safety, an enhanced preventive maintenance optimization model based on a three-stage failure process is proposed. Preventive maintenance is still a dominant maintenance policy due to its easy implementation. In order to correspond to the three-color scheme commonly used in practice, the lifetime of system before failure is divided into three stages, namely, normal, minor defective, and severe defective stages. When the minor defective stage is identified, two measures are considered for comparison: one is that halving the inspection interval only when the minor defective stage is identified at the first time; the other one is that if only identifying the minor defective stage, the subsequent inspection interval is halved. Maintenance is implemented immediately once the severe defective stage is identified. Minimizing the expected cost per unit time is our objective function to optimize the inspection interval. Finally, a numerical example is presented to illustrate the effectiveness of the proposed models.


2014 ◽  
Vol 988 ◽  
pp. 653-658
Author(s):  
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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