We provide a compact survey and brief interpretations and comments on some 170 publications on process capability indices which appeared in widely scattered sources during the years 1992 to 2000. A...

Process capability indices- a review. 1992–2000

https://ir.nctu.edu.tw:443/bitstream/11536/7703/1/000264002300010.pdf

An overview of theory and practice on process capability indices for quality assurance

Process capability indices (PCIs) are powerful means of studying the process ability for manufacturing a product that meets specifications. Several capability indices including C p , C pu , C pl and C pk have been widely used in manufacturing industry to provide common quantitative measures on process potential and performance. The formulas for these indices are easily understood and can be straightforwardly applied. However, those process capability indices are inappropriate for asymmetric tolerances and could not be applied to evaluate multiprocess products. Based on C p , C pu , C pl and C pk , this research aims to develop one process capability analysis chart (PCAC) for precisely measuring an entire product composed of symmetric tolerances, asymmetric tolerances, larger-the-better and smaller-the-better characteristics. The process capability analysis chart evaluates the capabilities of multi-process products and provides chances for continuous improvement on the manufacturing process.

https://ir.nctu.edu.tw:443/bitstream/11536/29283/1/000171985900016.pdf

Process capability analysis for an entire product

Process capability indices (PCIs) are tools widely used by the industries to determine the quality of their products and the performance of their manufacturing processes. Classic versions of these indices were constructed for processes whose quality characteristics have a normal distribution. In practice, many of these characteristics do not follow this distribution. In such a case, the classic PCIs must be modified to take into account the non-normality. Ignoring the effect of this non-normality can lead to misinterpretation of the process capability and ill-advised business decisions. An asymmetric non-normal model that is receiving considerable attention due to its good properties is the Birnbaum–Saunders (BS) distribution. We propose, develop, implement and apply a methodology based on PCIs for BS processes considering estimation, parametric inference, bootstrap and optimization tools. This methodology is implemented in the statistical software {\tt R}. A simulation study is conducted to evaluate its ...

Capability indices for Birnbaum–Saunders processes applied to electronic and food industries

The concept of generalized confidence intervals is used to derive lower confidence limits for some of the commonly used process capability indices. For the cases where approximate lower confidence limits are already available, numerical comparisons are made among the available approximations and the generalized lower confidence limit. The numerical results indicate that the generalized confidence interval does provide coverage probabilities very close to the nominal confidence level. Two examples are given to illustrate the results. Copyright © 2006 John Wiley & Sons, Ltd.

Generalized confidence intervals for process capability indices

Summary The process capability index Cpk has been widely used in manufacturing industry to provide numerical measures of process potential and performance. As noted by many quality control researchers and practitioners, Cpk is yield-based and is independent of the target T. This fails to account for process centering with symmetric tolerances, and presents an even greater problem with asymmetric tolerances. To overcome the problem, several generalizations of Cpk have been proposed to handle processes with asymmetric tolerances. Unfortunately, these generalizations understate or overstate the process capability in many cases, so reflect the process potential and performance inaccurately. In this paper, we first introduce a new index Cp"k, which is shown to be superior to the existing generalizations of Cpk. We then investigate the statistical properties of the natural estimator of Cp"k, assuming that the process is normally distributed.

https://ir.nctu.edu.tw:443/bitstream/11536/31716/1/000077830800008.pdf

K. S. Chen

Papers

New generalization of process capability index Cpk