A new exponentially weighted moving average chart with an adaptive control scheme for high yield processes—An application in injection molding process

Abstract

Abstract Analytical formulae for computing the average time to signal (ATS) value for the exponentially weighted moving average (EWMA) cumulative count of conforming (CCC) chart using the Markov chain procedure are derived, as the performance of this chart is currently studied using simulation in the literature. Additionally, the variable sampling interval (VSI) EWMA CCC chart for monitoring the cumulative counts of items inspected until a nonconforming item is obtained in a high yield process and is developed to increase the sensitivity of the basic EWMA CCC chart. By using the Markov chain procedure, optimal parameters of the VSI EWMA CCC chart in minimizing the ATS value are obtained and provided to facilitate the chart's implementation in practice. It is found that the VSI EWMA CCC chart shows an impressive improvement over the basic CCC, VSI CCC, and EWMA CCC charts. An example using real data from an injection molding process producing micro‐prism array of an optical element is given to demonstrate the implementation of the VSI EWMA CCC chart in practice. The originality of this manuscript lies in the derivation of new Markov chain‐based analytical formulae for computing the ATS of the EWMA CCC chart and the incorporation of the VSI technique into the EWMA CCC chart to boost the out‐of‐control detection speed of the latter.

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