A comparative study of two proposed CCC-r charts for high quality processes and their application to an injection molding process. Issue Volume 28:Issues 4(2016) (1st October 2016)

• Record Type: Journal Article
• Authors: Joekes, Silvia; Smrekar, Marcelo; Righetti, Andrea F.
• Is Part Of: Quality engineering. Volume 28:Issues 4(2016)
• Page Start: 467
• Page End: 475
• Publication Date: 2016-10-01
• Subjects: average run length (ARL) -- car parts plant -- CCC-r control charts -- high-quality processes -- negative binomial distribution; Quality control -- Periodicals; Production management -- Quality control -- Periodicals; 658.5
• DOI: 10.1080/08982112.2016.1172092
• Languages: English
• ISSNs: 0898-2112

Abstract

ABSTRACT: High-quality industrial processes, characterized by a low fraction of non-conforming items, require paying special attention to the statistical control methods employed since traditional Shewhart's control charts are no longer suitable. In this article, CCC- r charts are considered based on the cumulative count of conforming items inspected until r non-conforming items are observed. However, even though these charts have shown to be useful for high-quality processes, they are characterized by a biased average run length (ARL). In order to help engineers interested in this control methodology to select the best option, a computational study of statistical validation was performed to compare the two most outstanding procedures for the cases r = 2, 3, and 4. The performance was evaluated based on the ARL under control. The application of the CCC- r chart to a real process is shown with data from an automobile parts plant. Finally, analysis and discussion of the results are presented.