Abstract
This paper aims to compare the performances of modified confidence intervals based on robust scale estimators with classical confidence interval for process capability index (Cp) when the process has a non-normal distribution. The estimated coverage probability and the average width of the confidence intervals were obtained by a Monte-Carlo simulation under different scenarios. Simulation results showed that the modified confidence intervals performed well in terms of coverage probability and average width for all cases. Two real-life numerical examples from industry are analyzed to illustrate the performance and the implementation of the classical and modified confidence intervals for the process capability index (Cp) which also supported the results of the simulation study to some extent.
Similar content being viewed by others
References
Abu-Shawiesh MO (2008) A simple robust control chart based on MAD. J Math Stat 4(2):102–107
Abu-Shawiesh MO, Kibria BMG (2011) On some confidence intervals for estimating the population median: an empirical study. Int J Appl Math 24(2):161–182
Akyüz HE, Gamgam H (2017) Interval estimation for nonnormal population variance with kurtosis coefficient based on trimmed mean. Türkiye Klinikleri J Biostat 9(3):213–221
Akyüz HE, Gamgam H, Yalçınkaya A (2017) Interval estimation for the difference of two independent nonnormal population variances. Gazi University J Sci 30(3):117–129
Almonte C, Kibria BMG (2009) On some classical, bootstrap and transformation confidence intervals for estimating the mean of an asymmetrical population. Model Assist Stat Appl 4(2):91–104
Andersson PG (2004) Alternative confidence intervals for the total of a skewed biological population. Ecology 85:3166–3171
Baklizi A, Kibria BMG (2009) One and two sample confidence intervals for estimating the mean of skewed populations: an empirical comparative study. J Appl Stat 36:601–609
Balamurali S, Kalyanasundaram M (2002) Bootstrap lower confidence limits for the process capability indices Cp, Cpk and Cpm. International J Qual Reliabil Manage 19:1088–1097
Bittanti and Moiraghi (1998) Application of non-normal process capability indices to semiconductor quality control. IEEE Trans Semicond Manuf 11(2):296–303
Chang YS, Choi IS, Bai DS (2002) Process capability indices for skewed populations. Qual Reliabil Eng Int 18(5):383–393
Chao M, Lin DKJ (2006) Another look at the process capability index. Qual Reliabil Eng Int 22(2):153–163
Chen JP, Ding CG (2001) A new process capability index for non-normal distributions. Int J Qual Reliabil Manag 18(7):762–770
Chen K, Pearn W (1997) An application of non-normal process capability indices. Qual Reliabil Eng Int 13(6):335–360
David HA (1968) Gini`s mean difference rediscovered. Biometrika 55:573–575
Ding J (2004) A method of estimating the process capability index from the first four moments of non-normal data. Qual Reliabil Eng Int 20(8):787–805
Gini, C. (1912). Variabilitia e Mutabilitia, Contribututoallo Studiodelle distribuzioni e dellerelazoine Statistiche. Studion Economicoiuredice dell’Universitiadie Cagliari 3(Part 2) i–iii: 3–159
Gastwirth JL (1982) Statistical properties of a measure of tax assessment uniformity. J Stat Plan Inference 6:1–12
Gerstenberger and Vogel (2014) On the efficiency of Gini’s mean difference. Stat Methods Appl 24(4):569–596
Hampel FR (1974) The influence curve and its role in robust estimation. J Am Stat Assoc 69(436):383–393
Juran JM (1974) Jurans quality control handbook, 3rd edn. McGraw-Hill, New York
Kane VE (1986) Process capability indices. J Qual Technol 18(1):41–52
Khalilloo B, Shahriari H, Roghanian E (2017) Robust estimation of process capability. In: 13th International conference on Industrial Engineering, Mazandaran University of Science and Technology. pp 22–23
Kotz S, Lovelace C (1998) Process capability indices in theory and practice. Arnold, London
Leiva V, Marchant C, Saulo H, Aslam M, Rojas F (2014) Capability indices for birnbaum_saunders processes applied to electronic and food industries. J Appl Stat 41:1881–1902
Maiti, Saha (2012) On generalized quality capability index. In: Special 8th triennial symposium proceedings, vol 65, pp 257–260
Nanthakumar and Vijayalakshmi (2015) Construction of inter quartile range (iqr) control chart using process capability for mean using range. Int J Sci Eng Technol Res (IJSETR) 5(1):114–118
Piña-Monarrez MR, Ortiz-Yañez JF, Rodríguez-Borbón MI (2015) Non- normal capability indices for the weibull and lognormal distributions. Qual Reliabil Eng Int 32(4):1321–1329
Rezaie K, Taghizadeh MR, Ostadi B (2006) A practical implementation of the process capability indices. J Appl Sci 6(5):1182–1185
Rousseeuw PJ, Croux C (1993) Alternatives to the median absolute deviation. J Am Stat Assoc 88(424):1273–1283
Senvar O, Sennaroglu B (2016) Comparing performances of clements, box- cox, johnson methods with weibull distributions for assessing process capability. J Ind Eng Manage 9(3):634–642
Stigler SM (1973) Studies in the history of probability and statistics. XXXII laplace, fisher, and the discovery of the concept of sufficiency. Biometrika 60:439–445
Tiku ML, Akkaya AD (2004) Robust estimation and hypothesis testing. New Age International (P) Limited, New Delhi
Wooluru Y, Swamy DR, Nagesh P (2014) The process capability analysis tool for process performance measures and metrics-a case study. Int J Qual Res 8(3):399–416
Wooluru Y, Swamy DR, Nagesh P (2015) Process capability estimation for non-normal distributed data using robust methods-A comparative study. Int J Qual Res 10(2):407–420
Wu and Messimer (1999) A weighted variance capability index for general non-normal processes. Qual Reliabil Eng Int 15:397–402
Zhang J (2010) Conditional confidence intervals of process capability indices following rejection of preliminary tests. PhD Thesis, The University of Texas, Arlington
Zhou S, Dinh P (2005) Nonparametric confidence intervals for the one and two sample problems. Biostatistic 6:187–200
Acknowledgements
Authors are grateful to two anonymous referees and editor in chief for their invaluable constructive comments and suggestions, which certainly improved the quality and presentation of the paper greatly.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Abu-Shawiesh, M.O.A., Banik, S., Golam Kibria, B.M. et al. A comparison of some modified confidence intervals based on robust scale estimators for process capability index. Prod. Eng. Res. Devel. 14, 217–229 (2020). https://doi.org/10.1007/s11740-019-00939-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11740-019-00939-7