Failure rate monitoring in generalized gamma-distributed process. Issue 6 (2nd November 2021)

• Record Type: Journal Article
• Authors: Chakraborty, Niladri; Mahmood, Tahir
• Is Part Of: Quality technology & quantitative management. Volume 18:Issue 6(2021)
• Page Start: 718
• Page End: 739
• Publication Date: 2021-11-02
• Subjects: Average time to signal -- generalized gamma distribution -- high-quality processes -- statistical process control -- time-between-events; Quality control -- Periodicals; Quality control -- Statistical methods -- Periodicals; Industrial management -- Periodicals; Industrial management; Management -- Research -- Methodology -- Periodicals; Qualitative research -- Periodicals; Management; Quality control; Quality control -- Statistical methods; Periodicals; 658.00721
• DOI: 10.1080/16843703.2021.1953241
• Languages: English
• ISSNs: 1684-3703

Abstract

ABSTRACT: Advancement in technology brings a revolutionary change in the quality of the final product or items. Most of the manufacturing processes produce a large number of conforming items along with a few non-conforming items. For real-time monitoring of these highly efficient processes, monitoring of time-between-events is a well-known approach adopted in the literature of statistical process control. Usually, it is assumed that the time-between-events follows an exponential or gamma distribution. However, the generalized gamma distribution is the most popular choice for modelling skewed data. In this article, we consider a two-sided monitoring scheme based on the generalized gamma distribution. Two-sided monitoring schemes for skewed distributions often encounter bias in its run length properties. Therefore, we address this problem with modified control limits in a more general distributional setup. A Monte Carlo simulation-based study is designed, and results showed encouraging performance properties. A couple of practical applications in connection to monitoring renewable energy and coal mine explosions have been discussed.