Abstract
In this article, we consider six process capability indices (PCIs) whose quality characteristics have a normal distribution, out of which first PCI
Funding statement: This work is supported by the IoE (Ref. No./IoE/2024-25/12/FRP), Department of Statistics, Faculty of Mathematical Sciences, University of Delhi.
Acknowledgements
The author thanked the Editor in Chief and the Reviewer for their very careful reading and constructive comments which helped us to improve the earlier version of this article.
References
[1]
L. K. Chan, S. W. Cheng and F. A. Spiring,
A new measure of process capability:
[2] J. P. Chen and L. I. Tong, Bootstrap confidence interval of the difference between two process capability indices, Int. J. Adv. Manuf. Technol. 21 (2003), 249–256. 10.1007/s001700300029Suche in Google Scholar
[3] S. W. Cheng and F. A. Spiring, Assessing process capability: A Bayesian approach, IEE Trans. 21 (1989), 97–98. 10.1080/07408178908966212Suche in Google Scholar
[4] V. da Costa Soares, N. Jerez-Lillo, P. H. Ferreira and P. L. Ramos, Improved process capability assessment through semiparametric piecewise modeling, J. Stat. Comput. Simul. 94 (2024), no. 14, 3063–3092. 10.1080/00949655.2024.2366364Suche in Google Scholar
[5]
S. Dey and M. Saha,
Bootstrap confidence intervals of generalized process capability index
[6]
S. Dey and M. Saha,
Bootstrap confidence intervals of process capability index
[7]
S. Dey, M. Saha, S. S. Maiti and C.-H. Jun,
Bootstrap confidence intervals of generalized process capability index
[8]
S. Dey, W. Wang and M. Saha,
Modified estimation and confidence intervals of an asymmetric loss based process capability index
[9] T. C. Hsiang and G. Taguchi, A tutorial on quality control and assurance, Annual Meeting on the American Statistical Association, Las Vegas (1985), unpublished presentation. Suche in Google Scholar
[10] R. Ihaka and R. Gentleman, R: A language for data analysis and graphics, J. Comput. Graph. Statist. 5 (1996), 299–314. 10.1080/10618600.1996.10474713Suche in Google Scholar
[11] A. Jeang, C.-P. Chung, H-C. Li and M.-H. Sung, Process capability index for off-line application of product life cycle, Proceedings of the World Congress on Engineering 2008, Vol. II, London (2008). Suche in Google Scholar
[12] J. M. Juran, Juran’s Quality Control Handbook, 3rd ed., McGraw-Hill, New York, 1974. Suche in Google Scholar
[13] S. Kumar, M. Saha and S. Tyagi, Parametric confidence intervals of generalized process capability index and its applications, Life Cycle Reliab. Safety Eng. 11 (2022), 177–187. 10.1007/s41872-022-00194-3Suche in Google Scholar
[14] V. Leiva, C. Marchant, H. Saulo, M. Aslam and F. Rojas, Capability indices for Birnbaum–Saunders processes applied to electronic and food industries, J. Appl. Stat. 41 (2014), no. 9, 1881–1902. 10.1080/02664763.2014.897690Suche in Google Scholar
[15] T. Mathew, G. Sebastian and K. M. Kurian, Generalized confidence intervals for process capability indices, Qual. Reliab. Eng. Int. 23 (2007), 471–481. 10.1002/qre.828Suche in Google Scholar
[16] M. Saha, Applications of a new process capability index to electronic industries, Comm. Statist. 8 (2022), no. 4, 574–587. 10.1080/23737484.2022.2107962Suche in Google Scholar
[17] M. Saha, A. Devi, A. S. Yadav and S. S. Maiti, Evaluation of a novel loss-based process capacity index and its applications, Int. J. Syst. Assurance Eng. Manag. 15 (2024), 2188–2201. 10.1007/s13198-023-02235-1Suche in Google Scholar
[18]
M. Saha, S. Dey and S. S. Maiti,
Bootstrap confidence intervals of
[19]
M. Saha, S. Dey and S. Nadarajah,
Parametric inference of the process capability index
[20]
M. Saha, S. Dey and L. Wang,
Parametric inference of the loss based index
[21]
M. Saha, S. Dey, A. S. Yadav and S. Ali,
Confidence intervals of the index
[22]
M. Saha, S. Dey, A. S. Yadav and S. Kumar,
Classical and Bayesian inference of
[23] J. J. H. Shiau, C. T. Chiang and H. N. Hung, A Bayesian procedure for process capability assessment, Qual. Reliab. Eng. Int. 15 (1999), 369–378. 10.1002/(SICI)1099-1638(199909/10)15:5<369::AID-QRE262>3.0.CO;2-RSuche in Google Scholar
[24] J.-J. H. Shiau, H.-N. Hung and C.-T. Chiang, A note on Bayesian estimation of process capability indices, Statist. Probab. Lett. 45 (1999), no. 3, 215–224. 10.1016/S0167-7152(99)00061-9Suche in Google Scholar
[25] S. Weerahandi, Generalized confidence intervals, J. Amer. Statist. Assoc. 88 (1993), no. 423, 899–905. 10.1080/01621459.1993.10476355Suche in Google Scholar
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Artikel in diesem Heft
- Frontmatter
- Profit and Reliability Analysis of a Gas Production Unit with the Concept of Optimal Age Replacement Policy: A Copula Approach
- A Comprehensive Analysis Using Maximum Likelihood Estimation and Artificial Neural Networks for Modeling Arthritic Pain Relief Data
- A Comparative Study of Six Process Capability Indices and Their Applications to Electronic and Food Industries
- Estimation of a New Asymmetry Based Process Capability Index 𝐶𝑐 for Gamma Distribution
- Double and Group Acceptance Sampling Inspection Plans Based on Truncated Life Test for the Quasi-Xgamma Distribution
- E-Bayesian Estimation of the Weighted Power Function Distribution with Application to Medical Data
- Comparing Ridge Regression Estimators: Exploring Both New and Old Methods
Artikel in diesem Heft
- Frontmatter
- Profit and Reliability Analysis of a Gas Production Unit with the Concept of Optimal Age Replacement Policy: A Copula Approach
- A Comprehensive Analysis Using Maximum Likelihood Estimation and Artificial Neural Networks for Modeling Arthritic Pain Relief Data
- A Comparative Study of Six Process Capability Indices and Their Applications to Electronic and Food Industries
- Estimation of a New Asymmetry Based Process Capability Index 𝐶𝑐 for Gamma Distribution
- Double and Group Acceptance Sampling Inspection Plans Based on Truncated Life Test for the Quasi-Xgamma Distribution
- E-Bayesian Estimation of the Weighted Power Function Distribution with Application to Medical Data
- Comparing Ridge Regression Estimators: Exploring Both New and Old Methods