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Joint Economic Design of CUSUM Control Chart and Age-Based Imperfect Preventive Maintenance Policy

机译：CUSUM控制图和基于年龄的不完善预防性维护策略的联合经济设计

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摘要

The close relationship between statistical process control and maintenance has attracted lots of researchers to focus on the jointly economic design of control chart (a main tool of statistical process control) and preventive maintenance policy, andmuch progress has been made in this field. However, in the existing literatures, the (X) over bar chart is used most, and other charts are rarely considered. In this paper, the economic design of CUSUM chart and age-based imperfect preventive maintenance policy is presented. The process is considered as a multiphase system, and a recursive algorithm is used to model each phase. Besides, a sampling policy under the non-Markovian deterioration assumption is employed, and an age-based imperfect preventive maintenance policy is used. An optimization model with the objective of minimizing the expected cost per unit time is constructed to obtain the nearoptimal solution of decision variables: the age of the machine for maintenance, the number of age-based maintenances, sample size, sampling intervals, and the decision interval coefficient and reference value coefficient of CUSUM chart. The solution procedure of the model is provided. Also, sensitivity analysis is performed on the decision variables for each of the various parameters.
机译：统计过程控制与维护之间的密切关系吸引了许多研究者将重点放在控制图（统计过程控制的主要工具）和预防性维护策略的联合经济设计上，并且在这一领域已取得了很大进展。但是，在现有文献中，使用（X）over条形图最多，而很少考虑使用其他图。本文介绍了CUSUM图表的经济设计和基于年龄的不完善的预防性维护策略。该过程被视为一个多阶段系统，并且使用递归算法对每个阶段进行建模。此外，采用非马尔可夫恶化假设下的抽样策略，并使用基于年龄的不完善预防性维护策略。构建了一个旨在使单位时间的预期成本最小化的优化模型，以获取决策变量的最佳解决方案：维护机器的年龄，基于维护的维护次数，样本量，采样间隔和决策CUSUM图的区间系数和参考值系数。提供了模型的求解过程。而且，针对各种参数中的每一个对决策变量执行敏感性分析。

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  • 来源
    《Mathematical Problems in Engineering》 |2018年第7期|9246372.1-9246372.11|共11页
  • 作者

    Li Yaping; Chen Zhen; Pan Ershun;

  • 作者单位

    Nanjing Forestry Univ, Coll Econ & Management, Nanjing, Jiangsu, Peoples R China;

    Shanghai Jiao Tong Univ, Dept Ind Engn & Management, Shanghai, Peoples R China;

    Shanghai Jiao Tong Univ, Dept Ind Engn & Management, Shanghai, Peoples R China;

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