Distributional and Inferential Properties of the Estimated Precision Cp Based on Multiple Samples

Distributional and Inferential Properties of the Estimated Precision Cp Based on Multiple Samples Process precision index Cp has been widely used in the manufacturing industry to provide numerical measures on process potential. Pearn et al. (1998) considered an unbiased estimator of Cp for one single sample. They showed that the unbiased estimator is the UMVUE. They also proposed an efficient test for Cp based on one single sample, and showed that the test is the UMP test. In this paper, we consider an unbiased estimator of Cp for multiple samples. We show that the unbiased estimator is the UMVUE of Cp, which is asymptotically efficient. We also consider an efficient test for Cp, and show that the test is the UMPtest for multiple samples. The practitioners can use the proposed test on theirin-plant applications to obtain reliable decisions. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Quality & Quantity Springer Journals

Distributional and Inferential Properties of the Estimated Precision Cp Based on Multiple Samples

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Publisher
Kluwer Academic Publishers
Copyright
Copyright © 2003 by Kluwer Academic Publishers
Subject
Social Sciences; Methodology of the Social Sciences; Social Sciences, general
ISSN
0033-5177
eISSN
1573-7845
D.O.I.
10.1023/A:1027331308515
Publisher site
See Article on Publisher Site

Abstract

Process precision index Cp has been widely used in the manufacturing industry to provide numerical measures on process potential. Pearn et al. (1998) considered an unbiased estimator of Cp for one single sample. They showed that the unbiased estimator is the UMVUE. They also proposed an efficient test for Cp based on one single sample, and showed that the test is the UMP test. In this paper, we consider an unbiased estimator of Cp for multiple samples. We show that the unbiased estimator is the UMVUE of Cp, which is asymptotically efficient. We also consider an efficient test for Cp, and show that the test is the UMPtest for multiple samples. The practitioners can use the proposed test on theirin-plant applications to obtain reliable decisions.

Journal

Quality & QuantitySpringer Journals

Published: Oct 17, 2004

References

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