Statistical Performance of a Control Chart for Individual Observations Monitoring the Ratio of Two Normal Variables

• Published in: Quality and reliability engineering international Vol. 30; no. 8; pp. 1361 - 1377
• Main Authors: Celano, G., Castagliola, P., Faraz, A., Fichera, S.
• Format: Journal Article
• Language: English
• Published: Bognor Regis Blackwell Publishing Ltd 01-12-2014; Wiley Subscription Services, Inc; Wiley
• Subjects: average run length; Charts; Control charts; Dispersions; Mathematical models; Monitoring; Quality control; ratio; Raw materials; Shewhart control chart; standardization; Statistical Process Control; Statistics; Tables
• ISSN: 0748-8017; 1099-1638
• DOI: 10.1002/qre.1558

Statistical Process Control monitoring of the ratio Z of two normal variables X and Y has received too little attention in quality control literature. Several applications dealing with monitoring the ratio Z can be found in the industrial sector, when quality control of products consisting of several raw materials calls for monitoring their proportions (ratios) within a product. Tables about the statistical performance of these charts are still not available. This paper investigates the statistical performance of a Phase II Shewhart control chart monitoring the ratio of two normal variables in the case of individual observations. The obtained results show that the performance of the proposed chart is a function of the distribution parameters of the two normal variables. In particular, the Shewhart chart monitoring the ratio Z outperforms the (p = 2) multivariate T2 control chart when a process shift affects the in‐control mean of X or, alternatively, of Y and the correlation among X and Y is high and when the in‐control means of X and Y shift contemporarily to opposite directions. The sensitivity of the proposed chart to a shift of the in‐control dispersion has been investigated, too. We also show that the standardization of the two variables before computing their ratio is not a good practice due to a significant loss in the chart's statistical performance. An illustrative example from the food industry details the implementation of the ratio control chart. Copyright © 2013 John Wiley & Sons, Ltd.