Adaptive Control Limits for Bivariate Process Monitoring

Abstract

Variables control charts implement process state testing by separately assessing the measures of central tendency and spread. This work, based on the ideas of bivariate process control, analyzes whether the standard charting method could be considered as optimal and presents an alternative mode of process evaluation—biparameter description in terms of the joint distribution of sample averages and standard deviations. Thus it becomes possible to benefit from the advantages of this approach and at the same time to overcome its main shortcoming, namely lack of diagnostic ability. The proposed single X̄ chart with adaptive control limits provides a reliable tool for recognizing process state and indicating the parameter responsible for an out-of-control state. Additionally, the proposed method does not require a constant sample size during data collection.

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