Design and implementation of ARL-unbiased CCCr-chart for monitoring high-yield processes. (14th June 2022)

• Record Type: Journal Article
• Authors: Kumar, Nirpeksh; Singh, Ranjeet Kumar
• Is Part Of: International journal of quality engineering and technology. Volume 8:Number 4(2022)
• Page Start: 351
• Page End: 365
• Publication Date: 2022-06-14
• Subjects: average run length -- ARL -- ARL-unbiased -- control chart -- high-yield processes -- in-control performance -- out-of-control performance -- geometric distribution -- fraction non-conforming -- uniformly most powerful unbiased -- UMPU -- UMPU test; Engineering -- Quality control -- Periodicals; Systems engineering -- Periodicals; 620.0045
• Languages: English
• ISSNs: 1757-2177

Abstract

In this paper, we consider the -charts for monitoring the high-quality processes considering the cumulative counts of conforming (CCC) items up to the r th non-conforming one. But the charts perform poorly in detection of small downward shifts in the fraction non-conforming because of their undesirable ARL-biased property. In this paper, we eliminate the ARL-biasedness property and propose the ARL-unbiased charts using the notion of uniformly most powerful unbiased (UMPU) test to ensure that a user will get an OOC signal more quickly than a false alarm for the shifts in both upward and downward directions. The performance of the proposed chart is also compared with the existing ARL-unbiased CCC chart and it is found that the former has an improved ability of detecting shifts in the fraction non-conforming over the latter. An illustrative example is given and a summary and conclusions are offered.