Adaptive sampling interval cause-selecting control charts

Abstract

This article considers the statistical adaptive process control for two dependent process steps. We construct an adaptive sampling interval Z X control chart to monitor the quality variable produced by the first process step, and use the adaptive sampling interval Z e control chart to monitor the specific quality variable produced by the second process step. By using the proposed adaptive sampling interval control charts, we can quickly detect and distinguish which process step is out of control. The performance of the proposed adaptive sampling interval control charts is measured by the adjusted average time to signal (AATS), which was derived by a Markov chain approach, for an out-of-control process. An empirical automobile braking system example shows the application and the performance of the proposed adaptive sampling control charts in detecting shifts in process means. Some numerical results obtained demonstrated that the performance of the proposed adaptive sampling cause-selecting control charts outperforms the fixed sampling interval cause-selecting control charts.