The C” pk index for asymmetric tolerances: Implications and inference

W. L. Pearn, P. C. Lin and K. S. Chen

Metrika: International Journal for Theoretical and Applied Statistics, 2004, vol. 60, issue 2, 119-136

Abstract: The process capability index C pk has been widely used in the manufacturing industry to provide numerical measures on process performance. Since C pk is a yield-based index which is independent of the target T, it fails to account for process centering with symmetric tolerances, and presents an even greater problem with asymmetric tolerances. Pearn and Chen (1998) considered a new generalization C” pk which was shown to be superior to other existing generalizations of C pk for processes with asymmetric tolerances. In this paper, we investigate the relation between the fraction nonconforming and the value of C” pk . Furthermore, we derive explicit forms of the cumulative distribution function and the probability density function for the natural estimator ” pk , under the assumption of normality. We also develop a decision making rule based on the natural estimator ” pk , which can be used to test whether the process is capable or not. Copyright Springer-Verlag 2004

Keywords: Asymmetric tolerance; Decision making rule; Normally distributed process; Process yield (search for similar items in EconPapers)
Date: 2004
References: Add references at CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://hdl.handle.net/10.1007/s001840300300 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:metrik:v:60:y:2004:i:2:p:119-136

Ordering information: This journal article can be ordered from
http://www.springer.com/statistics/journal/184/PS2

DOI: 10.1007/s001840300300

Access Statistics for this article

Metrika: International Journal for Theoretical and Applied Statistics is currently edited by U. Kamps and Norbert Henze

More articles in Metrika: International Journal for Theoretical and Applied Statistics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().