Loading...

A transformation technique to estimate the process capability index for non-normal processes

Hosseinifard, S. Z ; Sharif University of Technology

657 Viewed
  1. Type of Document: Article
  2. DOI: 10.1007/s00170-008-1376-x
  3. Abstract:
  4. Estimating the process capability index (PCI) for non-normal processes has been discussed by many researches. There are two basic approaches to estimating the PCI for non-normal processes. The first commonly used approach is to transform the non-normal data into normal data using transformation techniques and then use a conventional normal method to estimate the PCI for transformed data. This is a straightforward approach and is easy to deploy. The alternate approach is to use non-normal percentiles to calculate the PCI. The latter approach is not easy to implement and a deviation in estimating the distribution of the process may affect the efficacy of the estimated PCI. The aim of this paper is to estimate the PCI for non-normal processes using a transformation technique called root transformation. The efficacy of the proposed technique is assessed by conducting a simulation study using gamma, Weibull, and beta distributions. The root transformation technique is used to estimate the PCI for each set of simulated data. These results are then compared with the PCI obtained using exact percentiles and the Box-Cox method. Finally, a case study based on real-world data is presented. © 2008 Springer-Verlag London Limited
  5. Keywords:
  6. Computer peripheral equipment ; Interfaces (computer) ; Process control ; Production engineering ; Weibull distribution ; Beta distributions ; Box-Cox transformation and quintile-based capability indices ; Non-normal datum ; Non-normal process ; Process capability index ; Real-world datum ; Root transformation ; Simulated datum ; Simulation studies ; Transformation techniques ; Weibull ; Fourier transforms
  7. Source: International Journal of Advanced Manufacturing Technology ; Volume 40, Issue 5-6 , 2009 , Pages 512-517 ; 02683768 (ISSN)
  8. URL: https://link.springer.com/article/10.1007%2Fs00170-008-1376-x