An integrated quick-switch sampling system based on a process capability index for constructing a solid supplier-buyer relationship
To-Cheng Wang,
Bi-Min Hsu and
Ming-Hung Shu
International Journal of Production Research, 2022, vol. 60, issue 21, 6413-6429
Abstract:
The quick-switch sampling (QSS) systems based on process capability index (PCI) have been proved to be useful for inspecting processes streaming at a low level of defects because of their small sizes required and dynamic responsiveness to problems. However, most of the recent studies have aimed at deriving the mathematical model and comparing performances for the acceptance criteria-type QSS system, and only a few of them have an interest in the development of the required sample-size-type QSS system; their studies have limited simultaneous discussions on both systems’ advantages and disadvantages, not to mention the lack of investigations on the impact of the joint application of the two QSS system types. In this paper, an integrated QSS (IQSS) system based on the most popular PCI was proposed; the system can accommodate two existing types of PCI-based QSS systems and further boost the sampling performance and discriminatory power. Moreover, by operating suitable types of PCI-based QSS systems in different stages of the supplier-buyer partnership, a progressive lot-disposition strategy was introduced to construct a solid supplier-buyer relationship. We also developed a web-based tool to accurately and efficiently execute all types’ PCI-based QSS systems. Finally, the industrial applicability was demonstrated in a case study.
Date: 2022
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2021.1991598 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:tprsxx:v:60:y:2022:i:21:p:6413-6429
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20
DOI: 10.1080/00207543.2021.1991598
Access Statistics for this article
International Journal of Production Research is currently edited by Professor A. Dolgui
More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().