ON TECHNIQUES FOR IDENTIFICATION OF OUT-OF-CONTROL VARIABLE(S) IN MULTIVARIATE T2 CONTROL CHART ON CABLE PRODUCTION

Multivariate statistical process control charts are used for process monitoring and control of two or more variables simultaneously for quality and quality improvement. A popular multivariate control chart is used to monitor the mean vector of the process. A usual problem in the multivariate control chart is the identification and interpretation of variable(s) for an out-of-control signal that occurred in the chart. This has brought many developed techniques from many researchers to aid in finding the responsible variable(s) that caused the out-of-control signal in the chart. This work is aimed at a comparative study of some developed techniques for identifying and interpreting an out-of-control signal, in the multivariate control chart when applied on the cable production process. The techniques are Mason-Tracy-Young, Donganaksoy-Faltin-Tucker, Univariate -chart using Bonferroni control limits by Alt and Principal component analysis by Jackson. A performance criterion, the power of the test was used to ascertain the most satisfactory technique that explained the out-of-control signal that occurred in -chart. From the results and discussions, Mason Tracy-Young and Doganaksoy-Faltin-Tucker techniques are the most satisfactory for identifying and interpreting an out-of-control signal in the multivariate control chart.