Bridging the gap between theory and practice in basic statistical process monitoring

References

• Albers, W., and W. C. M. Kallenberg. 2004. Are estimated control charts in control? Statistics 38 (1):67–79.
   Web of Science ®Google Scholar
• Alwan, L. C., and H. V. Roberts. 1988. Time-series modeling for statistical process control. Journal of Business & Economic Statistics 6 (1):87–95.
   Web of Science ®Google Scholar
• Antzoulakos, D. L., and A. C. Rakitzis. 2008. The revised m-of-k runs rules. Quality Engineering 20:75–81.
   Google Scholar
• Box, G. E. P., and S. Narasimhan. 2010. Rethinking statistics for quality control. Quality Engineering 22:60–72.
   Web of Science ®Google Scholar
• Box, G., and J. Ramírez. 1992. Cumulative score charts. Quality and Reliability Engineering International 8:17–27.
   Google Scholar
• Capizzi, G. 2015. Recent advances in process monitoring: Nonparametric and variable-selection methods for phase I and phase II. Quality Engineering 27:44–67.
   Web of Science ®Google Scholar
• Champ, C. W., and W. H. Woodall. 1987. Exact results for Shewhart control charts with supplementary runs rules. Technometrics 29 (4):393–399.
   Web of Science ®Google Scholar
• Colosimo, B. 2011. Statistical process control for geometric specifications. Chapter 8 in Statistical analysis of profile monitoring, ed. by R. Noorossana, A. Saghaei, A. Amiri, 217–252.
   Google Scholar
• Colosimo, B. M., P. Cicorella, M. Pacella, and M. Blaco. 2014. From profile to surface monitoring: SPC for cylindrical surfaces via Gaussian processes. Journal of Quality Technology 46 (2):95–113.
   Web of Science ®Google Scholar
• Davis, R. B., and W. H. Woodall. 1988. Performance of the control chart trend rule under linear shift. Journal of Quality Technology 20 (4):260–262.
   Web of Science ®Google Scholar
• Davis, R. B., and W. H. Woodall. 2002. Evaluating and improving the synthetic control chart. Journal of Quality Technology 34 (2):200–208.
   Web of Science ®Google Scholar
• De Ketelaere, B., T. Rato, E. Schmitt, and M. Hubert. 2016. Statistical process monitoring in data rich environments. Quality Engineering 28 (1):127–142.
   Web of Science ®Google Scholar
• Deming, W. E. 1993. The new economics for industry, government, and education. Cambridge, MA: Massachusetts Institute of Technology Center for Advanced Engineering Study.
   Google Scholar
• Gandy, A., and J. T. Kvaløy. 2013. Guaranteed conditional performance of control charts via bootstrap methods. Scandinavian Journal of Statistics 40:647–668.
   Web of Science ®Google Scholar
• Gandy, A., and F. D.-H. Lau. 2013. Non-restarting cumulative sum charts and control of the false discovery rate. Biometrika 100 (1):261–268.
   Web of Science ®Google Scholar
• Grant, E. L. 1946. Statistical quality control. New York, NY: McGraw-Hill.
   Google Scholar
• Hoerl, R. W. 2000. Discussion of “Controversies and contradictions in statistical process control.” Journal of Quality Technology 32 (4):351–355.
   Web of Science ®Google Scholar
• Jensen, W. A., S. D. Grimshaw, and B. Espen. 2015. Case studies: nonlinear profile monitoring for oven temperature data. Journal of Quality Technology 48 (1):84–97.
   Web of Science ®Google Scholar
• Johnson, N. L. 1961. A Simple theoretical approach to cumulative sum control charts, Journal of the American Statistical Association 56:835–840.
   Web of Science ®Google Scholar
• Jones, M. A., and S. H. Steiner. 2012. Assessing the effect of estimation error on the risk-adjusted CUSUM chart performance. International Journal for Quality in Health Care 24 (2):176–181.
   PubMed Web of Science ®Google Scholar
• Jones-Farmer, L. A., W. H. Woodall, S. H. Steiner, and C. W. Champ. 2014. An overview of phase I analysis for process improvement and monitoring. Journal of Quality Technology 46 (3):265–280.
   Web of Science ®Google Scholar
• Kenett, R. S., and M. Pollack. 2012. On assessing the performance of sequential procedures for detecting a change. Quality and Reliability Engineering international 28:500–507.
   Web of Science ®Google Scholar
• Knoth, S. 2016. A critique of synthetic control charts. Journal of Quality Technology 48 (2): 178–195.
   Google Scholar
• Mahmoud, M. A., G. R. Henderson, E. K. Epprecht, and W. H. Woodall. 2010. Estimating the standard deviation in quality control applications. Journal of Quality Technology 42 (4):348–357.
   Web of Science ®Google Scholar
• Maragah, H. D., and W. H. Woodall. 1992. The effect of autocorrelation on the retrospective X-chart. Journal of Statistical Computation and Simulation 40:29–42.
   Google Scholar
• Mao, H., C. N. Ginther, and W. H. Woodall. 2016. An evaluation of Wheeler's method for monitoring the rate of rare events. To appear in Quality and Reliability Engineering International. DOI: 10.1002/qre.2024
   Google Scholar
• Montgomery, D. C. 2013. Introduction to statistical quality control 7th ed. Hoboken, NJ: John Wiley & Sons.
   Google Scholar
• Nair, V. N. 2013. Deming lecture, joint statistical meetings. Montreal, Canada.
   Google Scholar
• Nazir, H. Z., M. Schoonhoven, M. Riaz, and R. J. M. M. Does. 2014. Quality quandaries: A stepwise approach for setting up a robust Shewhart location control chart. Quality Engineering 26:246–252.
   Web of Science ®Google Scholar
• Nelson, L. S. 1982. Control charts for individual measurements. Journal of Quality Technology 14 (3):172–173.
   Web of Science ®Google Scholar
• Noorossana, R., A. Saghaei, and A. Amiri. (eds.) 2011. Statistical analysis of profile monitoring. Hoboken, NJ: John Wiley & Sons, Inc.
   Google Scholar
• Poor, H. V., and O. Hadjiliadis. 2009. Quickest detection. Cambridge, UK: Cambridge University Press.
   Google Scholar
• Psarakis, S., and G. E. A. Papaleonida. 2007. SPC procedures for monitoring autocorrelated processes. Quality Technology and Quantitative Management 4:501–540.
   Google Scholar
• Rigdon, S. E., E. N. Cruthis, and C. W. Champ. 1994. Design strategies for individuals and moving range control charts. Journal of Quality Technology 26 (4):274–287.
   Web of Science ®Google Scholar
• Saleh, N. A., M. A. Mahmoud, L. A. Jones-Farmer, I. Zwetsloot, and W. H. Woodall. 2015b. Another look at the EWMA control chart with estimated parameters”. Journal of Quality Technology 47 (4):363–382.
   Web of Science ®Google Scholar
• Saleh, N. A., M. A. Mahmoud, M. J. Keefe, and W. H. Woodall. 2015a. The difficulty in designing X-bar and X- control charts with estimated parameters. Journal of Quality Technology 47 (2):127–138.
   Web of Science ®Google Scholar
• Schoonhoven, M., and R. J. M. M Does. 2013. A robust X-bar control chart. Quality and Reliability Engineering International 29:951–970.
   Web of Science ®Google Scholar
• Schoonhoven, M., M. Riaz, and J. M. M. Does. 2011. Design and analysis of control charts for standard deviation with estimated parameters”. Journal of Quality Technology 43 (4):307–333.
   Web of Science ®Google Scholar
• Sego, L. H., W. H. Woodall, and M. R., Jr. Reynolds. 2008. A comparison of surveillance methods for small incidence rates. Statistics in Medicine 27 (8):1225–1247.
   PubMed Web of Science ®Google Scholar
• Shewhart, W. A. 1931. Economic control of manufactured product. New York, NY: D. Van Nostrand Company, Inc. (Reprinted in 1980 by American Society for Quality Control, Milwaukee, WI).
   Google Scholar
• Shewhart, W. A. 1939. Statistical method from the viewpoint of quality control, ed. by W. E. Deming. Washington DC: Graduate School of the Department of Agriculture.
   Google Scholar
• Shiryayev, A. N. 2010. Quickest detection problems: Fifty years later. Sequential Analysis 29 (4):345–385.
   Google Scholar
• Steinberg, D. 2015. Industrial statistics: The challenges and the research. Quality Engineering 28 (1):45–59.
   Google Scholar
• Steiner, S. H., and J. MacKay. 2000. Discussion of “Controversies and contradictions in statistical process control.” Journal of Quality Technology 32 (4):370–372.
   Web of Science ®Google Scholar
• Steiner, S. H., and R. J. MacKay. 2005. Statistical engineering: an algorithm for reducing variation in manufacturing processes. Milwaukee, WI: ASQ Quality Press.
   Google Scholar
• Taguchi, G., S. Chowdhury, and Y. Yu. 2001. The Mahalanobis-Taguchi system. New York: McGraw-Hill.
   Google Scholar
• Tartakovsky, I. Nikiforov, and M. Basseville. 2015. Sequential analysis—hypothesis testing and changepoint detection. Boca Raton, FL: CRC Press.
   Google Scholar
• Thyregod, P., and J. Iwersen. 2000. Discussion of “Controversies and contradictions in statistical process control.” Journal of Quality Technology 32 (4):375–376.
   Web of Science ®Google Scholar
• Vardeman, S. B. 1999. A brief tutorial on the estimation of the process standard deviation. IIE Transactions 31:503–507.
   Web of Science ®Google Scholar
• Wheeler, D. J. 1995. Advanced topics in statistical process control—the power of Shewhart's charts. Knoxville TN: SPC Press.
   Google Scholar
• Wheeler, D. J. 1996. What about charts for count data? Quality Digest July, 50–51. (www.qualitydigest.com/jul/spctool.html).
   Google Scholar
• Wheeler, D. J. 2000. Discussion of “Controversies and contradictions in statistical process control.” Journal of Quality Technology 32 (4):361–363.
   Web of Science ®Google Scholar
• Wheeler, D. J. 2011a. What about p-charts? When should we use specialty charts for count data. Quality Digest (www.qualitydigest.com/inside/quality-insider-article/what-about-p-charts.html).
   Google Scholar
• Wheeler, D. J. 2011b. Working with rare events. Quality Digest (www.qualitydigest.com/inside/quality-insider-article/working-rare-events.html).
   Google Scholar
• Wheeler, D. J. 2011c. Myths About Process Behavior Charts: How to avoid some common obstacles to good practice. Quality Digest (www.qualitydigest.com/inside/quality-insider-article/myths-about-process-behavior-charts.html).
   Google Scholar
• Wheeler, D. J. 2014a. Why use ranges? What they didn't teach in your stat class. Quality Digest (www.qualitydigest.com/print/24685).
   Google Scholar
• Wheeler, D. J. 2014b. Statistics and SPC: Two things sharing a common name can be different. Quality Digest (www.qualitydigest.com/inside/quality-insider-column/statistics-and-spc.html#).
   Google Scholar
• Wheeler, D. J. 2015. Probability Limits: a long standing controversy. Quality Digest (www.qualitydigest.com/inside/quality-insider-column/probability-limits.html).
   Google Scholar
• Woodall, W. H. 1986. Weaknesses of the economic design of control charts. Letter to the Editor, Technometrics 28:408–410.
   Web of Science ®Google Scholar
• Woodall, W. H. 2000. Controversies and contradictions in statistical process control (with discussion). Journal of Quality Technology 32 (4):341–378.
   Web of Science ®Google Scholar
• Woodall, W. H., and Adams, B. M. 1993. The statistical design of CUSUM charts. Quality Engineering 5 (4):559–570.
   Google Scholar
• Woodall, W. H., and A. G. Driscoll. 2015a. Some recent results on monitoring the rate of a rare event”, Frontiers in statistical quality control 11. ed. by S. Knoth and W. Schmid, 15–27. Heidelberg, Germany: Springer.
   Google Scholar
• Woodall, W. H., and F. W. Faltin. 1996. An overview and perspective on control charting. Chapter 2 of Statistical applications in process control, ed. by J. B. Keats and D. C. Montgomery, 7–20. Marcel-Dekker: Arizona State University.
   Google Scholar
• Woodall, W. H., S. L. Fogel, and S. H. Steiner. 2015b. The monitoring and improvement of surgical outcome quality. Journal of Quality Technology 47 (4):383–399.
   Web of Science ®Google Scholar
• Woodall, W. H., and D. C. Montgomery. 2014. Some current directions in the theory and application of statistical process monitoring. Journal of Quality Technology 46 (1):78–94.
   Web of Science ®Google Scholar
• Woodall, W. H., K.-L. Tsui, and G. R. Tucker. 1997. A review of statistical and fuzzy control charts based on categorical data. Frontiers in statistical quality control 5, ed. by H.-J. Lenz, and P.-T. Wilrich, 83–89. Heidelberg, Germany: Physica-Verlag.
   Google Scholar
• Woodall, W. H., M. Zhao, K. Paynabar, R. Sparks, and J. D. Wilson. 2016. An overview and perspective on social network monitoring. To appear in IIE Transactions.
   Google Scholar