On the conditional decision procedure for high yield processes

Cumulative Count of Conforming (CCC) items chart has shown to be an effective tool for monitoring high yield processes. However, this chart uses a single count value to determine whether a change in a process has occurred. This makes the chart relatively insensitive to process shifts. To improve the performance of the chart, values of the previous runs or observations were incorporated into the decision rule using conditional probability. This paper investigates the performance of the modified decision rule and shows that the results obtained for the average run length are only true for the case of independent observations. An appropriate relationship for the average run length is developed and the results are compared to the modified decision rule mathematically and numerically. The results indicate that the average run length values obtained from the modified decision rule always underestimates the true values.