A double-sampling SPM scheme for simultaneously monitoring of location and scale shifts and its joint design with maintenance strategies. (January 2020)

• Record Type: Journal Article
• Authors: Huang, Shuo; Yang, Jun; Xie, Min
• Is Part Of: Journal of manufacturing systems. Volume 54(2020)
• Page Start: 94
• Page End: 102
• Publication Date: 2020-01
• Subjects: Joint design -- SPM scheme -- Double-sampling -- Maintenance strategy -- Location shift -- Scale shift; Manufacturing processes -- Periodicals; Production engineering -- Data processing -- Periodicals; Robots, Industrial -- Periodicals; Production, Technique de la -- Informatique -- Périodiques; Robots industriels -- Périodiques; Electronic journals; 670.42
• DOI: 10.1016/j.jmsy.2019.11.009
• Languages: English
• ISSNs: 0278-6125

Abstract

Highlights: A new doubel-sampling monitoring scheme is proposed for simultaneously monitoring of location and scale shifts. We construct a joint design model by integrating our proposed monitoring scheme with maintenance strategies. Comparison results show that our proposed model is more economical than the traditional one. Abstract: Joint design of SPM (Statistical Process Monitoring) and maintenance strategies has evolved as a popular research topic in industrial engineering. Most existing works only consider location shifts of a process but neglect the effects of scale shifts. Besides, traditional SPM schemes are usually employed based on the single-sampling plan, which might be insensitive to detect quality shifts and perform uneconomically from the cost-saving perspective. To overcome the drawbacks mentioned above, this paper proposes a double-sampling SPM scheme for simultaneously monitoring of location and scale shifts, and then develop a more realistic and effective model for the joint design of SPM and maintenance strategies. First, we propose a new SPM scheme with a double-sampling plan for simultaneously monitoring location and scale shifts. The comparison results indicate that our proposed DS (double-sampling) scheme has a faster detection speed than the single-sampling one for different combination of shifts. Therefore, we combine our proposed SPM scheme with two widely used maintenance strategies: corrective maintenance and prevent maintenance, and then construct a new cost model under the constraints of sample size, operation time and A R L (average run length). A real case study is implemented to verify the effectiveness of the proposed method. Results demonstrate that the proposed model is more economical than the traditional method.