, University of Cincinnati
Industrial Engineering, Sharif University of Technology
In this paper, a Multivariate-Multistage Quality Control (MVMSQC) procedure is investigated. In this procedure discriminate analysis, linear regression and control chart theory are combined to control the means of correlated characteristics of a process, which involves several serial stages. Furthermore, the quality of the output at each stage depends on the output of the previous stage as well as the process of the current stage. The theoretical aspects and the applications of this procedure are enhanced and clarified and its performance is evaluated through a series of simulated data. Both in-control (type one error) and out-of-control (type two error) Average Run Length (ARL) studies are made and the performance of the MVMSQC methodology is discussed.