Development of the yield-based process capability index, C _py , to flexibly and accurately measure conformance

Abstract

Purpose

The purpose of this paper is to develop an yield-based process capability index (PCI), C _py , to overcome the shortcomings of existing PCIs that limit their use and lead to inaccurate measures of quality conformance under a variety of common conditions.

Design/methodology/approach

–C _py is developed conceptually to flexibly and accurately reflect conformance and then used to numerically measure inaccuracies of C _pk .

Findings

–C _py overcomes many of the problems associated with existing PCIs, including C _pk . The degree of process distribution non-normality, level of quality (the sigma level), and whether the process is centered or shifted left or right affect the direction and size of process capability error produced by C _pk . The accuracy of C _pk can be greatly affected by process data that deviate even slightly from normality.

Practical implications

–C _py offers numerous advantages compared to existing PCIs. It accurately reflects process conformance regardless of the process distribution. It is applicable even if the process has multiple characteristics and with both variable and attribute data. Its calculation is relatively simple and the necessary data for it are likely already captured by most organizations.

Originality/value

The main contributions are the development of a new PCI, C _py ; a conceptual analysis of its advantages; and a numerical analysis of the improved accuracy of C _py as compared to C _pk for shifted and non-shifted process means for normal, nearly normal, and highly non-normal distributions over a range of process variability levels.

Citation

Kenyon, G.N., Sale, R.S., Hozak, K. and Chiou, P. (2016), "Development of the yield-based process capability index, C _py , to flexibly and accurately measure conformance", International Journal of Quality & Reliability Management, Vol. 33 No. 7, pp. 882-899. https://doi.org/10.1108/IJQRM-01-2014-0011