Synthetic exponential control charts with unknown parameter

References

• Aly, A. A., Mahmoud, M. A., Woodall, W. H. (2015a). A comparison of the performance of phase II simple linear profile control charts when parameters are estimated. Communications in Statistics–Simulation and Computation 44(6):1432–1440.
   Google Scholar
• Aly, A. A., Saleh, N. A., Mahmoud, M. A., Woodall, W. H. (2015b). A re-evaluation of the adaptive exponentially weighted moving average control chart when parameters are estimated. Quality and Reliability Engineering International 31(8):1611–1622.
   Google Scholar
• Borror, C. M., Keats, J. B., Montgomery, D. C. (2003). Robustness of time between events CUSUM. International Journal of Production Research 41:3435–3444.
   Google Scholar
• Bourke, P. D. (1991). Detecting a shift in fraction nonconforming using run-length control charts with 100% inspection. Journal of Quality Technology 23:225–238.
   Google Scholar
• Calzada, M. E., Scariano, S. M. (2013). A synthetic control chart for the coefficient of variation. Journal of Statistical Computation and Simulation 83(5):853–867.
   Google Scholar
• Castagliola, P., Wu, S., Khoo, M. B. C., Chakraborti, S. (2014). Synthetic Phase II Shewhart-type attributes control charts when process parameters are estimated. Quality and Reliability Engineering International 30:315–335.
   Google Scholar
• Celano, G., Castagliola, P. (2016). A synthetic control chart for monitoring the ratio of two normal variables. Quality and Reliability Engineering International 32(2):681–696.
   Google Scholar
• Chan, L. Y., Xie, M., Goh, T. N. (2000). Cumulative quality control charts for monitoring production process. International Journal of Production Research 38:397–408.
   Google Scholar
• Chen, F. L., Huang, H. J. (2005). A synthetic chart for monitoring process dispersion with sample range. International Journal of Advanced Manufacturing Technology 26:842–851.
   Google Scholar
• Cheng, C. S., Chen, P. W. (2011). An ARL-unbiased design of time-between-events control charts with run rules. Journal of Statistical Computation and Simulation 81(7):857–871.
   Google Scholar
• Costa, A. F. B., Rahim, M. A. (2006). A synthetic control chart for monitoring the process mean and variance. Journal of Quality in Maintenance Engineering 12(1):81–88.
   Google Scholar
• Davis, R. B., Woodall, W. H. (2002). Evaluating and improving the synthetic control chart. Journal of Quality Technology 34:200–208.
   Google Scholar
• Fang, Y. Y., Khoo, M. B. C., Lee, M. H. (2013). Synthetic-type control charts for time-between-events monitoring. Plos One 8(6):1–13.
   Google Scholar
• Fang, Y. Y., Khoo, M. B. C., Teh, S. Y., Xie, M. (2016). Monitoring of time-between-events with a generalized group runs control chart. Quality and Reliability Engineering International 32(3): 767–781.
   Google Scholar
• Faraz, A., Woodall, W. H., Heuchenne, C. (2015). Guaranteed conditional performance of theS2 control chart with estimated parameters. International Journal of Production Research 53(14):4405–4413.
   Google Scholar
• Gandy, A., Kvaløy, J. T. (2013). Guaranteed conditional performance of control charts via bootstrap methods. Scandinavian Journal of Statistics 40:647–668.
   Google Scholar
• Guo, B., Wang, B. X., Cheng, Y. (2015). Optimal design of a synthetic chart for monitoring process dispersion with unknown in-control variance. Computers & Industrial Engineering 88:78–87.
   Google Scholar
• Huang, H. J., Chen, F. L. (2005). A synthetic chart for monitoring process dispersion with sample standard deviation. Computers & Industrial Engineering 49:221–240.
   Google Scholar
• Jensen, W. A., Jones-Farmer, L. A., Champ, C. W., Woodall, W. H. (2006). Effects of parameter estimation on control chart properties: A literature review. Journal of Quality Technology 38:349–364.
   Google Scholar
• Jones, M. A., Steiner, S. H. (2012). Assessing the effect of estimation error on risk-adjusted CUSUM chart performance. International Journal for Quality in Health Care 24:176–181.
   Google Scholar
• Kumar, N., Chakraborti, S. (2016). Phase II Shewhart-type control charts for monitoring times between events and effects of parameter estimation. Quality and Reliability Engineering International 32(1):315–328.
   Google Scholar
• Lee, J., Wang, N., Xu, L., Schuh, A., Woodall, W. H. (2013). The effect of parameter estimation on upper-sided Bernoulli cumulative sum charts. Quality and Reliability Engineering International 29:639–651.
   Google Scholar
• Lee, M. H., Khoo, M. B. C. (2014). The synthetic mean square error control chart. Communications in Statistics—Simulation and Computation 43:1523–1542.
   Google Scholar
• Lucas, J. M. (1985). Counted Data CUSUMs. Technometrics 27(2):129–144.
   Google Scholar
• Montgomery, D. C. (2012). Introduction to Statistical Quality Control. New Jersey: John Wiley.
   Google Scholar
• Ozsan, G., Testik, M. C., Weiß, C. H. (2010). Properties of the exponential EWMA chart with parameter estimation. Quality and Reliability Engineering International 26:555–569.
   Google Scholar
• Psarakis, S., Vyniou, A. K., Castagliola, P. (2014). Some recent developments on the effects of parameter estimation on control charts. Quality and Reliability Engineering International 30:1113–1129.
   Google Scholar
• Rakitzis, A. C. (2017). On the performance of modified runs rules X charts with estimated parameters. Communications in Statistics—Simulation and Computation 46(2):1360–1380.
   Google Scholar
• Rakitzis, A. C. (2016). Monitoring exponential data using two-sided control charts with runs rules. Journal of Statistical Computation and Simulation 86:149–159.
   Google Scholar
• Saleh, N. A., Mahmoud, M. A., Jones-Farmer, L. A., Zwetsloot, I., Woodall, W. H. (2015a). Another look at the EWMA control chart with estimated parameters. Journal of Quality Technology 47(4):363–382.
   Google Scholar
• Saleh, N. A., Mahmoud, M. A., Keefe, M. J., Woodall, W. H. (2015b). The difficulty in designing Shewhart and X control charts with estimated parameters. Journal of Quality Technology 47(2):127–138.
   Google Scholar
• Santiago, E., Smith, J. (2013). Control charts based on the exponential distribution: Adapting runs rules for the t chart. Quality Engineering 25:85–96.
   Google Scholar
• Scariano, S. M., Calzada, M. E. (2003). A note on the lower-sided synthetic chart for exponentials. Quality Engineering 15:677–680.
   Google Scholar
• Scariano, S. M., Calzada, M. E. (2009). The generalized synthetic chart. Sequential Analysis 28:54–68.
   Google Scholar
• Teoh, W. L., Khoo, M. B. C., Castagliola, P., Lee, M. H. (2016). The exact run length distribution and design of the Shewhart chart with estimated parameters based on median run length. Communications in Statistics—Simulation and Computation 45(6):2081–2103.
   Google Scholar
• Woodall, W. H., Montgomery, D. C. (2014). Some current directions in the theory and application of statistical process monitoring. Journal of Quality Technology 46(1):78–94.
   Google Scholar
• Wu, Z., Spedding, T. A. (2000). A synthetic control chart for detecting small shifts in the process mean. Journal of Quality Technology 32:32–38.
   Google Scholar
• Xie, M., Goh, T. N., Ranjan, P. (2002). Some effective control chart procedures for reliability monitoring. Reliability Engineering and System Safety 77:143–150.
   Google Scholar
• Yang, J., Yu, H., Cheng, Y., Xie, M. (2015). Design of exponential control charts based on average time to signal using a sequential sampling scheme. International Journal of Production Research 53(7):2131–2145.
   Google Scholar
• Zhang, C. W., Xie, M., Goh, T. N. (2006). Design of exponential control charts using a sequential sampling scheme. IIE Transactions 38:1105–1116.
   Google Scholar
• Zhang, M., Megahed, F. M., Woodall, W. H. (2014). Exponential CUSUM charts with estimated control limits. Quality and Reliability Engineering International 30:275–286.
   Google Scholar
• Zhang, M., Peng, Y., Schuh, A., Megahed, F. M., Woodall, W. H. (2013). Geometric charts with estimated control limits. Quality and Reliability Engineering International 29:209–223.
   Google Scholar