Optimal multi-level classification and preventive maintenance policy for highly reliable products. Issue 8 (18th April 2017)

• Record Type: Journal Article
• Authors: Chen, Zhen; Xia, Tangbin; Pan, Ershun
• Is Part Of: International journal of production research. Volume 55:Issue 8(2017)
• Page Start: 2232
• Page End: 2250
• Publication Date: 2017-04-18
• Subjects: highly reliable products -- classification -- preventive maintenance policy -- optimisation -- degradation-based burn-in; Factory management -- Periodicals; 658.57
• DOI: 10.1080/00207543.2016.1232497
• Languages: English
• ISSNs: 0020-7543

Abstract

Abstract : Highly reliable products are widely used in aerospace, automotive, integrated manufacturing and other fields. With increasing market demand and competition, product classification for different segment market segments has become more and more critical. Leading manufacturers are always searching and designing classification policies for highly reliable products. On the other hand, preventive maintenance can improve the operation efficiency of the product, extend the service life and reduce enormous losses brought by failures. These two factors are taken into account by many large enterprises when making sound economical and operational decisions. Therefore, this research proposes a joint multi-level classification and preventive maintenance model (JMCPM model) under age-based maintenance. Different preventive maintenance policies are developed for corresponding level units. Accordingly, the optimal joint policy of multi-level classification and preventive maintenance can be obtained by JMCPM. In this model, degradation-based burn-in is utilised to eliminate defective units and collect degradation data. The degradation data are the basis of classification and can be used to estimate the residual life. Then, for making full use of these data, linear discriminant analysis is employed to design classification rules. The objective of the JMCPM model is to minimise the average cost per unit time by properly choosing the settings of classification and preventive maintenance intervals simultaneously. Finally, a simulation study is carried out for evaluating the performance of the JMCPM model. For an illustration of the proposed model and the methods of inference developed here, a real case involving degradation data from electrical connectors is analysed.