A PROPOSED ENHANCEMENT FOR THE SHORT RUNS MULTIVARIATE CONTROL CHART FOR THE PROCESS MEAN

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Date
2006-03
Authors
FOO, NG THEAM
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Multivariate control charts are gaining attention because in practice, most processes involve the monitoring of several correlated variables. The most well known multivariate process monitoring method is the Hotelling's T 2 control chart. The Hotelling's T 2 control chart is used in process monitoring which involves mass production where the data to estimate the mean vector and covariance matrix are readily available. Recently, manufacturing industries tend to produce products in smaller lot sizes or low volume production. Such a production is known as short runs production or more commonly known as short runs. Short runs are becoming more important as a result of increased emphasis on just-in-time techniques, synchronous manufacturing, job-shop settings and the reduction of in-process inventory and costs. Thus, to enable the Hotelling's T 2 chart to be used in short runs, modifications of the Hotelling's T 2 statistics are required. The existing short runs multivariate charts for the process mean are based on individual measurements. In this thesis, a method to enhance the performance of the short runs multivariate control chart will be proposed for the case where the process covariance matrix is unknown and need to be estimated. The proposed method is based on the use of a robust estimator of the modified mean square successive differences (MSSD), replacing the sample covariance matrix estimator. The performance of the enhanced chart will be compared to that of the existing chart. The simulation results show that the enhanced chart gives superior results. An example is also given to show how the enhanced chart is used in a real situation.
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A PROPOSED ENHANCEMENT FOR THE SHORT RUNS MULTIVARIATE CONTROL
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