A general model for the economic-statistical design of adaptive control charts for processes subject to multiple assignable causes

George Nenes, Konstantinos A. Tasias and Giovanni Celano

International Journal of Production Research, 2015, vol. 53, issue 7, 2146-2164

Abstract: Fully adaptive control charts are efficient statistical process control means to monitor a quality characteristic affecting the outcome of a manufacturing process. Usually, the performance of these adaptive charts is investigated in processes characterised by the possibility of the occurrence of a single assignable cause. However, this assumption is frequently far from reality, because a process shift to the out-of-control condition can be the consequence of several assignable causes, which can occur at the same time or independently. In this paper, we investigate the economic-statistical design of a variable-parameter (Vp) Shewhart control chart monitoring the process mean in the presence of multiple assignable causes. We develop a Markov chain that models the occurrence of several assignable causes leading to progressive process deterioration and calling for different corrective actions. A benchmark of examples has been generated to compare the performance of the Vp control chart with other adaptive control charts and the fixed-parameter control chart. The obtained results reveal the economic superiority of the Vp control chart.

Date: 2015
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DOI: 10.1080/00207543.2014.974850

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