A EWMA control chart based on an auxiliary variable and repetitive sampling for monitoring process location

References

• Abbas, N., M. Riaz, and R. J. Does. 2013. Mixed exponentially weighted moving average–cumulative sum charts for process monitoring. Quality and Reliability Engineering International 29 (3): 345–356.
   Google Scholar
• Abbas, N., M. Riaz, and R. J. M. M. Does. 2011. Enhancing the performance of EWMA charts. Quality and Reliability Engineering International 27 (6):821–833.
   Google Scholar
• Ahmad, L., et al. 2014. Designing of X-bar control charts based on process capability index using repetitive sampling. Transactions of the Institute of Measurement and Control 36 (3):367–374.
   Google Scholar
• Ahmad, L., et al. 2016. Dispersion chart for some popular distributions under repetitive sampling. Journal of Advanced Mechanical Design Systems and Manufacturing 10 (4):1–18.
   Google Scholar
• Ahmad, L., et al. 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):971–980.
   Google Scholar
• Ahmad, L., M. Aslam, and M. Azam. 2015. Developing variables repetitive group sampling control chart using regression estimator. in 13th International Conference on Statistical Sciences Statistics: Future Risks, Challenges and Developments on March 16–18, 2015. 2015. Islamia College, Peshawar Khyber Pakhtunkhwa, Pakistan: ISOSS, Lahore, Pakistan.
   Google Scholar
• Ahmad, S., et al. 2014. On efficient use of auxiliary information for control charting in SPC. Computers & Industrial Engineering 67:173–184.
   Google Scholar
• Aslam, M., et al. 2011. Variable repetitive group sampling plans with process loss consideration. Journal of Statistical Computation and Simulation 81:1417–1432.
   Google Scholar
• Aslam, M., et al. 2013. A mixed repetitive sampling plan based on process capability index. Applied Mathematical Modeling 37:10027–10035.
   Google Scholar
• Aslam, M., et al. 2014. Designing of a new monitoring t-chart using repetitive sampling. Information Sciences 269 (0):210–216.
   Google Scholar
• Aslam, M., et al. 2016. A control chart for COM–poisson distribution using resampling and exponentially weighted moving average. Quality and Reliability Engineering International 32:727–735.
   Google Scholar
• Aslam, M., et al. 2016. Multiple dependent state repetitive group sampling plan for Burr XII distribution. Quality Engineering 28 (2):1231–237.
   Google Scholar
• Aslam, M., et al. 2017. A control chart for multivariate Poisson distribution using repetitive sampling. Journal of Applied Statistics 44 (1):123–136.
   Google Scholar
• Azam, M., et al. 2016. Design of X-bar chart for Burr Distribution under the Repetitive Sampling. Science International (Lahore) 28 (4):3265–3271.
   Google Scholar
• Balamurali, S., and C. H. Jun. 2006. Repetitive group sampling procedure for variables inspection. Journal of Applied Statistics 33 (3):327–338.
   Google Scholar
• 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.
   Google Scholar
• Grover, L. K., and P. Kaur. 2014. A generalized class of ratio type exponential estimators of population mean under linear transformation of auxiliary variable. Communications in Statistics-Simulation and Computation 43 (7):1552–1574.
   Google Scholar
• Lee, H., et al. 2015. A control chart using an auxiliary variable and repetitive sampling for monitoring process mean. Journal of Statistical Computation and Simulation 85 (16):3289–3296.
   Google Scholar
• Lee, S.-H., and C.-H. Jun. 2012. A process monitoring scheme controlling false discovery rate. Communications in Statistics-Simulation and Computation 41 (10):1912–1920.
   Google Scholar
• Lee, S.-H., J.-H. Park, and C.-H. Jun. 2014. An exponentially weighted moving average chart controlling false discovery rate. Journal of Statistical Computation and Simulation 84 (8):1830–1840.
   Google Scholar
• Lucas, J. M., and M. S. Saccucci. 1990. Exponentially weighted moving average control schemes: properties and enhancements. Technometrics 32 (1):1–12.
   Google Scholar
• Montgomery, D.C. 2009. Introduction to statistical quality control. 6th ed, New York: John Wiley & Sons, Inc.
   Google Scholar
• Park, J.-H., and C.-H. Jun. 2012. Multivariate process control chart for controlling the false discovery rate. Industrial Engineering and Management Systems 11 (4):385–389.
   Google Scholar
• Riaz, M. 2008. Monitoring process mean level using auxiliary information. Statistica Neerlandica 62 (4): 458–481.
   Google Scholar
• Riaz, M. 2008. Monitoring process mean level using auxiliary information. Statistica Neerlandica 62 (4):458–481.
   Google Scholar
• Riaz, M. 2008. Monitoring process variability using auxiliary information. Computational Statistics 23 (2):253–276.
   Google Scholar
• Riaz, M., et al. 2013. On the performance of auxiliary‐based control charting under normality and nonnormality with estimation effects. Quality and Reliability Engineering International 29 (8):1165–1179.
   Google Scholar
• Riaz, M., N. Abbas, and R. J. Does. 2011. Improving the performance of CUSUM charts. Quality and Reliability Engineering International 27 (4):415–424.
   Google Scholar
• Saghir, A. 2015. Phase-I design scheme for -chart based on posterior distribution. Communications in Statistics – Theory and Methods 44 (3):644–655.
   Google Scholar
• Saghir, A., and Z. Lin. 2014. A flexible and generalized exponentially weighted moving average control chart for count data. Quality and Reliability Engineering International 30 (8):1427–1443.
   Google Scholar
• Saghir, A., and Z. Lin. 2014. Cumulative sum charts for monitoring the COM-poisson processes. Computers and Industrial Engineering 68:65–77.
   Google Scholar
• Santiago, E., and J. Smith. 2013. Control charts based on the exponential distribution: adapting runs rules for the t chart. Quality Engineering 25 (2):85–96.
   Google Scholar
• Sherman, R. E. 1965. Design and evaluation of a repetitive group sampling plan. Technometrics 7 (1):11–21.
   Google Scholar
• Singh, H. P., and R. S. Solanki. 2013. A new procedure for variance estimation in simple random sampling using auxiliary information. Statistical Papers 54 (2):479–497.
   Google Scholar
• Singh, R., and N. S. Mangat. 2013. Elements of survey sampling. vol. 15, Springer Science & Business Media.
   Google Scholar
• Sodipo, A. 2010. Difference-type and regression-type estimators for the population mean based on post-stratification and subsampling of the nonrespondents. European Journal of Scientific Research 43 (4):445–451.
   Google Scholar
• Yadav, S. 2011. Efficient estimators for population variance using auxiliary information. Global Journal of Mathematical Sciences: Theory and Practical 3 (4):369–376.
   Google Scholar