Design and implementation of ARL-unbiased CCCr-chart for monitoring high-yield processes. (14th June 2022) - Kumar, Nirpeksh; Singh, Ranjeet Kumar
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.