A multi-stage preventive maintenance optimization model for products with rectangular warranty region

Author(s):  
Huihui Zhu ◽  
Liying Wang
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.


2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Jianfei Ye ◽  
Huimin Ma

In order to solve the joint optimization of production scheduling and maintenance planning problem in the flexible job-shop, a multiobjective joint optimization model considering the maximum completion time and maintenance costs per unit time is established based on the concept of flexible job-shop and preventive maintenance. A weighted sum method is adopted to eliminate the index dimension. In addition, a double-coded genetic algorithm is designed according to the problem characteristics. The best result under the circumstances of joint decision-making is obtained through multiple simulation experiments, which proves the validity of the algorithm. We can prove the superiority of joint optimization model by comparing the result of joint decision-making project with the result of independent decision-making project under fixed preventive maintenance period. This study will enrich and expand the theoretical framework and analytical methods of this problem; it provides a scientific decision analysis method for enterprise to make production plan and maintenance plan.


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 ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2830 ◽  
Author(s):  
Chang Ye ◽  
Shihong Miao ◽  
Yaowang Li ◽  
Chao Li ◽  
Lixing Li

This paper presents a hierarchical multi-stage scheduling scheme for the AC/DC hybrid active distribution network (ADN). The load regulation center (LRC) is considered in the developed scheduling strategy, as well as the AC and DC sub-network operators. They are taken to be different stakeholders. To coordinate the interests of all stakeholders, a two-level optimization model is established. The flexible loads are dispatched by LRC in the upper-level optimization model, the objective of which is minimizing the loss of the entire distribution network. The lower-level optimization is divided into two sub-optimal models, and they are carried out to minimize the operating costs of the AC/DC sub-network operators respectively. This two-level model avoids the difficulty of solving multi-objective optimization and can clarify the role of various stakeholders in the system scheduling. To solve the model effectively, a discrete wind-driven optimization (DWDO) algorithm is proposed. Then, considering the combination of the proposed DWDO algorithm and the YALMIP toolbox, a hierarchical optimization algorithm (HOA) is developed. The HOA can obtain the overall optimization result of the system through the iterative optimization of the upper and lower levels. Finally, the simulation results verify the effectiveness of the proposed scheduling scheme.


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