修正质量损失法在考虑维修成本的产品质量特性分析中的应用

IF 2.3 2区工程技术 Q3 ENGINEERING, INDUSTRIAL

Quality Technology and Quantitative Management Pub Date : 2022-02-27 DOI:10.1080/16843703.2022.2044120

Kai Jin, Xintian Liu, Miao Liu, Kangfeng Qian

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引用次数: 4

摘要

摘要针对产品在实际维修时不能恢复为新，维修后降解率逐渐增加的问题。提出了产品质量特性在使用寿命期间服从多阶段线性变化的概念，可用于修正质量损失模型。考虑维修成本、质量损失与产品关键质量特征(KQC)范围之间的相关性，进一步调整产品的预防性维修(PM)计划以获得最佳的KQC范围。以空调空气轴承和活塞的故障数据为例。本文从质量损失和维修费用两个维度对在役设备的最佳预防性维修进行了比较分析。结果表明，最优的预防性维护范围可以降低企业的总运营成本。科学评价在役产品的使用寿命，合理安排产品的维护和退役工作，提高产品的利用率，为全生命周期的产品质量研究提供了新的视角。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Modified quality loss for the analysis of product quality characteristics considering maintenance cost

ABSTRACT In view of the fact that the product cannot be restored to new for the actual maintenance, and the degradation rate gradually increases after the maintenance. A concept, quality characteristics of products should obey a multi-stage linear variation during service life, is proposed, which can be used to modify the quality loss model. The correlation among maintenance cost, quality loss, and the range of key quality characteristics (KQC) of product is considered, products’ preventive maintenance (PM) schedules are further adjusted to obtain the optimal range of KQC. Failure data of the air bearing of the air conditioner and the piston are used as examples. This paper compares and analyzes the best preventive maintenance of in-service equipment from two dimensions of quality loss and maintenance cost. The results show that the optimal preventive maintenance range can reduce the total operating cost of enterprises. Scientific evaluation of the service life of in-service products, reasonable arrangement of product maintenance and decommissioning work, improved product utilization, and provided a new perspective for product quality research in the whole life cycle.

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来源期刊

Quality Technology and Quantitative Management ENGINEERING, INDUSTRIAL-OPERATIONS RESEARCH & MANAGEMENT SCIENCE

CiteScore

5.10

自引率

21.40%

发文量

审稿时长

>12 weeks

期刊介绍： Quality Technology and Quantitative Management is an international refereed journal publishing original work in quality, reliability, queuing service systems, applied statistics (including methodology, data analysis, simulation), and their applications in business and industrial management. The journal publishes both theoretical and applied research articles using statistical methods or presenting new results, which solve or have the potential to solve real-world management problems.