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A Resetting Scheme for Process Parameters using the Mahalanobis-Taguchi System
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 Title & Authors
A Resetting Scheme for Process Parameters using the Mahalanobis-Taguchi System
Park, Chang-Soon;
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Mahalanobis-Taguchi system(MTS) is a statistical tool for classifying the normal group and abnormal group in multivariate data structures. In addition to the classification itself, the MTS uses a method for selecting variables useful for the classification. This method can be used efficiently especially when the abnormal group data are scattered without a specific directionality. When the feedback adjustment procedure through the measurements of the process output for controlling process input variables is not practically possible, the reset procedure can be an alternative one. This article proposes a reset procedure using the MTS. Moreover, a method for identifying input variables to reset is also proposed by the use of the contribution. The identification of the root-cause parameters using the existing dimension-reduced contribution tends to be difficult due to the variety of correlation relationships of multivariate data structures. However, it became possible to provide an improved decision when used together with the location-centered contribution and the individual-parameter contribution.
Classification analysis;reset procedure;contribution;multivariate data;normal group;threshold;
 Cited by
메이저리그 타자들의 명예의 전당 입성과 탈락에 대한 Mahalanobis-Taguchi System의 적용과 비교,김수환;박창순;

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