Skip to main content
Log in

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

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Kane VE (1986) Process capability indices. J Qual Technol 18(1):41–52

    Google Scholar 

  2. Johnson NL (1949) Systems of frequency curves generated by methods of translation. Biometrika 36:149–176

    MATH  MathSciNet  Google Scholar 

  3. Box GEP, Cox DR (1964) An analysis of transformation. J R Stat Soc B 26:211–243

    MATH  MathSciNet  Google Scholar 

  4. Somerville SE, Montgomery DC (1996) Process capability indices and non-normal distributions. Qual Eng 9:305–316

    Article  Google Scholar 

  5. Rivera LAR, Hubele NF, Lawrence FP (1995) Cpk index estimation using data transformation. Comput Ind Eng 29:55–58

    Article  Google Scholar 

  6. Clements JA (1989) Process capability calculations for non-normal distributions. Qual Prog 22:95–100

    Google Scholar 

  7. Kotz S, Lovelace CR (1998) Introduction to process capability indices in theory and practice. Arnold, London

    Google Scholar 

  8. Wu HH, Wang JS, Liu TL (1998) Discussions of the Clements-based process capability indices. In: Proceedings of the 1998 CIIE National Conference, Chang-Hua, Taiwan, December 1998, pp 561–566

  9. Liu P-H, Chen F-L (2006) Process capability analysis of non-normal process data using the Burr XII distribution. Int J Adv Manuf Technol 27:975–984

    Article  Google Scholar 

  10. Choi IS, Bai DS (1996) Process capability indices for skewed populations. In: Proceedings of the 20th International Conference on Computer and Industrial Engineering, Kyongju, Korea, October 1996, pp 1211–1214

  11. Pal S (2004) Evaluation of nonnormal process capability indices using generalized lambda distribution. Qual Eng 17:77–85

    Article  Google Scholar 

  12. Castagliola P (1996) Evaluation of non-normal process capability indices using Burr’s distributions. Qual Eng 8(4):587–593

    Article  Google Scholar 

  13. Tang LC, Than SE (1999) Computing process capability indices for non-normal data: a review and comparative study. Qual Reliab Eng Int 15:339–353

    Article  Google Scholar 

  14. Wright PA (1995) A process capability index sensitive to skewness. J Stat Comput Simul 52:195–203

    Article  Google Scholar 

  15. Niaki STA, Abbasi B (2007) Skewness reduction approach in multi-attribute process monitoring. Commun Stat Theory Methods 36(12):2313–2325

    Article  MATH  MathSciNet  Google Scholar 

  16. English JR, Taylor GD (1993) Process capability analysis—a robustness study. Int J Prod Res 31:1621–1635

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Babak Abbasi.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Hosseinifard, S.Z., Abbasi, B., Ahmad, S. et al. A transformation technique to estimate the process capability index for non-normal processes. Int J Adv Manuf Technol 40, 512–517 (2009). https://doi.org/10.1007/s00170-008-1376-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-008-1376-x

Keywords

Navigation