Bootstrap Confidence Limits on Process Capability Indices

Author(s):  
Alan J. Collins
2017 ◽  
Vol 32 (2) ◽  
Author(s):  
Sebastian George ◽  
Ajitha Sasi

AbstractThis article is a comparative study between the parametric asymptotic lower confidence limits and bootstrap lower confidence limits for the basic quantile based process capability indices based on the unified super-structure


2012 ◽  
Vol 2012 ◽  
pp. 1-10
Author(s):  
Cheng Peng ◽  
Jiaqing Xu

We propose an asymptotic nonparametric confidence interval for quantile-based process capability indices (PCIs) based on the superstructure CNp(u,v) modified from Cp(u,v) which contains the four basic PCIs, Cp, Cpk, Cpm, and Cpmk, as special cases. Since the asymptotic variance of the estimator for quantile-based PCIs involves the density function of the underlying process, the existing asymptotic results cannot be used directly to construct confidence limits for PCIs. To obtain a consistent estimator for the asymptotic variance of the estimated quantile-based PCIs, in this paper, we propose to use the kernel density estimator for the underlying process. Consequently, the confidence limits for PCIs are established based on the consistent estimates. A real-life example from manufacturing engineering is used to illustrate the implementation of the proposed methods. Simulation studies are also presented in this paper to compare the two quantile estimators that are used in the definition of PCIs.


1990 ◽  
Vol 22 (3) ◽  
pp. 223-229 ◽  
Author(s):  
Youn-Min Chou ◽  
D. B. Owen ◽  
A. Salvador ◽  
A. Borrego

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