References
- Abujiya, M. R., M. Riaz, and M. H. Lee. 2015. Enhanced cumulative sum charts for monitoring process dispersion. PloS One 10 (4):e0124520. doi:https://doi.org/10.1371/journal.pone.0124520.
- Adeoti, O. A., and J. O. Olaomi. 2018. Capability index-based control chart for monitoring process mean using repetitive sampling. Communications in Statistics - Theory and Methods 47 (2):493–507. doi:https://doi.org/10.1080/03610926.2017.1307401.
- Ahmad, L., M. Aslam, and C.-H. Jun. 2014a. Coal quality monitoring with improved control charts. European Journal of Scientific Research 125 (2):427–34.
- Ahmad, L., M. Aslam, and C.-H. Jun. 2014b. Designing of X-bar control charts based on process capability index using repetitive sampling. Transactions of the Institute of Measurement and Control 36 (3):367–74. doi:https://doi.org/10.1177/0142331213502070.
- Ahmad, L., M. Aslam, and C.-H. Jun. 2016. The design of a new repetitive sampling control chart based on process capability index. Transactions of the Institute of Measurement and Control 38 (8):971–80. doi:https://doi.org/10.1177/0142331215571120.
- Ahmad, L., M. Aslam, O. H. Arif, and C. H. Jun. 2016. Dispersion chart for some popular distributions under repetitive sampling. Journal of Advanced Mechanical Design Systems and Manufacturing 10 (4):1–18.
- Amdouni, A.,. P. Castagliola, H. Taleb, and G. Celano. 2015. Monitoring the coefficient of variation using a variable sample size control chart in short production runs. The International Journal of Advanced Manufacturing Technology 81 (1-4):1–14. doi:https://doi.org/10.1007/s00170-015-7084-4.
- Aslam, M., M. Mohsin, and C.-H. Jun. 2016. A new t-chart using process capability index. Communications in Statistics-Simulation and Computation 46 (7):5141–5150.
- Aslam, M., M. Mohsin, and C.-H. Jun. 2017. A new t-chart using process capability index. Communications in Statistics - Simulation and Computation 46 (7):5141–5150. doi:https://doi.org/10.1080/03610918.2016.1146759.
- Aslam, M., O. H. Arif, and C.-H. Jun. 2017. An attribute control chart for a Weibull distribution under accelerated hybrid censoring. PloS One 12 (3):e0173406. doi:https://doi.org/10.1371/journal.pone.0173406.
- Azam, M., M. Aslam, and C.-H. Jun. 2015. Designing of a hybrid exponentially weighted moving average control chart using repetitive sampling. The International Journal of Advanced Manufacturing Technology 77 (9-12):1927–7. doi:https://doi.org/10.1007/s00170-014-6585-x.
- Castagliola, P., G. Celano, S. Fichera, and G. Nenes. 2013. The variable sample size t control chart for monitoring short production runs. The International Journal of Advanced Manufacturing Technology 66 (9-12):1353–1366.
- Chen, K., M. Huang, and R. Li. 2001. Process capability analysis for an entire product. International Journal of Production Research 39 (17):4077–4087. doi:https://doi.org/10.1080/00207540110073082.
- Cheng, C.-S., and P.-W. Chen. 2011. An ARL-unbiased design of time-between-events control charts with runs rules. Journal of Statistical Computation and Simulation 81 (7):857–871. doi:https://doi.org/10.1080/00949650903520944.
- Clements, J. A. 1989. Process capability calculations for non-normal distributions. Quality Progress 22 (9):95–97.
- David, H. 1968. Miscellanea: Gini’s mean difference rediscovered. Biometrika 55 (3):573–575. doi:https://doi.org/10.1093/biomet/55.3.573.
- Dey, S., M. Saha, S. S. Maiti, and C.-H. Jun. 2018. Bootstrap confidence intervals of generalized process capability index Cpyk for Lindley and power Lindley distributions. Communications in Statistics - Simulation and Computation 47 (1):249–262. doi:https://doi.org/10.1080/03610918.2017.1280166.
- Downton, F. 1966. Linear estimates with polynomial coefficient. Biometrika 53 (1-2):129–141. doi:https://doi.org/10.1093/biomet/53.1-2.129.
- Garcia-Diaz, J. C., and F. Aparisi. 2005. Economic design of EWMA control charts using regions of maximum and minimum ARL. IIE Transactions 37 (11):1011–1021. doi:https://doi.org/10.1080/07408170500232214.
- Gerstenberger, C., and D. Vogel. 2015. On the efficiency of Gini’s mean difference. Statistical Methods & Applications 24 (4):569–596. doi:https://doi.org/10.1007/s10260-015-0315-x.
- Gini, C. 1912. Variabilità e mutabilità: Contributo allo studio delle distribuzioni e relazioni statistiche [Variability and mutability: Contribution to the study of statistical distributions and relations]. Bologna: Tipogr. di P. Cuppini.
- Huang, P., and T. Hwang. 2005. The Inference of Gini’s Mean Difference. International Journal of Pure and Applied Mathematics 25 (1):39–48.
- Kane, V. E. 1986. Process Capability Indices. Journal of Quality Technology 18 (1):41–52. doi:https://doi.org/10.1080/00224065.1986.11978984.
- Khan, N., M. Aslam, L. Ahmad, and C.-H. Jun. 2017. A Control Chart for Gamma Distributed Variables Using Repetitive Sampling Scheme. Pakistan Journal of Statistics and Operation Research 13 (1):47–61. doi:https://doi.org/10.18187/pjsor.v13i1.1390.
- Knoth, S. 2007. Accurate ARL calculation for EWMA control charts monitoring normal mean and variance simultaneously. Sequential Analysis 26 (3):251–263. doi:https://doi.org/10.1080/07474940701404823.
- Lomnicki, Z. 1952. The standard error of Gini’s mean difference. The Annals of Mathematical Statistics 23 (4):635–637. doi:https://doi.org/10.1214/aoms/1177729346.
- Maravelakis, P. E., J. Panaretos, and S. Psarakis. 2005. An examination of the robustness to non normality of the EWMA control charts for the dispersion. Communications in Statistics - Simulation and Computation 34 (4):1069–1079. doi:https://doi.org/10.1080/03610910500308719.
- Montgomery, D. C. 2009. Introduction to Statistical Quality Control. 6th ed.. New York: John Wiley & Sons, Inc.
- Nair, U. 1936. The standard error of Gini’s mean difference. Biometrika 28 (3–4):428–436. doi:https://doi.org/10.1093/biomet/28.3-4.428.
- Nanthakumar, D., and M. Vijayalakshmi. 2015. Construction of interquartile range (IQR) control chart using process capability for mean. International Journal of Science, Engineering and Technology Research 5 (1):114–118.
- Nichols, M. D., and W. Padgett. 2006. A bootstrap control chart for Weibull percentiles. Quality and Reliability Engineering International 22 (2):141–151. doi:https://doi.org/10.1002/qre.691.
- Ong, H. C., and E. Alih. 2015. A control chart based on cluster-regression adjustment for retrospective monitoring of individual characteristics. PloS One 10 (4):e0125835. doi:https://doi.org/10.1371/journal.pone.0125835.
- Palmer, K., and K.-L. Tsui. 1999. A review and interpretations of process capability indices. Annals of Operations Research 87:31–47. doi:https://doi.org/10.1023/A:1018993221702.
- Pearn, W. L. 1998. New generalization of process capability index Cpk. Journal of Applied Statistics 25 (6):801–810. doi:https://doi.org/10.1080/02664769822783.
- Pearn, W., and K. Chen. 1997. Capability indices for non-normal distributions with an application in electrolytic capacitor manufacturing. Microelectronics Reliability 37 (12):1853–1858. doi:https://doi.org/10.1016/S0026-2714(97)00023-1.
- Riaz, M., and A. Saghirr. 2007. Monitoring process variability using Gini’s mean difference. Quality Technology & Quantitative Management 4 (4):439–454. doi:https://doi.org/10.1080/16843703.2007.11673164.
- Riaz, M., and R. J. Does. 2008. An alternative to the bivariate control chart for process dispersion. Quality Engineering 21 (1):63–71. doi:https://doi.org/10.1080/08982110802445579.
- Riaz, M., and S. A. Abbasi. 2009. Gini’s mean difference based time-varying. Economic Quality Control 24 (2):269–286. doi:https://doi.org/10.1515/EQC.2009.269.
- Saha, M., S. Dey, and S. S. Maiti. 2018. Parametric and non-parametric bootstrap confidence intervals of C Npk for exponential power distribution. Journal of Industrial and Production Engineering 35 (3):160–169. doi:https://doi.org/10.1080/21681015.2018.1437793.
- Sennaroglu, B., and O. Senvar. 2015. Performance comparison of box-cox transformation and weighted variance methods with weibull distribution. Journal of Aeronautics and Space TECHNOLOGIES 8 (2):49–55.
- Sullivan, L. P. 1984. Reducing variability: A new approach to quality. Quality Progress 17 (7):15–21.
- Yen, F. Y., K. M. B. Chong, and L. M. Ha. 2013. Synthetic-type control charts for time-between-events monitoring. PloS One. 8 (6):e65440. doi:https://doi.org/10.1371/journal.pone.0065440.
- Yitzhaki, S. 2003. Gini’s mean difference: A superior measure of variability for non-normal distributions. Metron 61 (2):285–316.