A Synthetic Exponentially Weighted Moving-average Chart for High-yield Processes

As charts to monitor the process fraction defectives, P, in the high-yield processes, Mishima et al. (2002) discussed a synthetic chart, the Synthetic CS chart, which integrates the CS (Confirmation Sample) CCC(Cumulative Count of Conforming)-r chart and the CCC-r chart. The Synthetic CS chart is designed to monitor quality characteristics in real-time. Recently, Kotani et al. (2005) presented the EWMA (Exponentially Weighted Moving-Average) CCC-r chart, which considers combining the quality characteristics monitored in the past with one monitored in real-time. In this paper, we present an alternative chart that is more superior to the EWMA CCC-r chart. It is an integration of the EWMA CCC-r chart and the CCC-r chart. In using the proposed chart, the quality characteristic is initially judged as either the in-control state or the out-of-control state, using the lower and upper control limits of the EWMA CCC-r chart. If the process is not judged as the in-control state by the EWMA CCC-r chart, the process is successively judged, using the CCC-r chart to confirm the judgement of the EWMA CCC-r chart. We compare the ANOS (Average Number of Observations to Signal) of the proposed chart with those of the EWMA CCC-r chart and the Synthetic CS chart. From the numerical experiments, with the small size of inspection items, the proposed chart is the most sensitive to detect especially the small shifts in P among other charts.

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