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Quality Technology & Quantitative Management Volume 14, 2017 - Issue 4: Advances in the Theory and Application of Statistical Process Control
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Original Articles

Systems for modern quality and business improvement

Douglas C. MontgomerySchool of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USACorrespondence[email protected]
&
Connie M. BorrorASU Foundation Professor of Statistics, School of Mathematical and Natural Sciences, New College of Interdisciplinary Arts and Sciences, Arizona State University West, Phoenix, AZ, USA
Pages 343-352 | Accepted 06 Mar 2017, Published online: 17 Apr 2017

References

  • Anderson-Cook, C. M., Lu, L., Clark, G., DeHart, S. P., Hoerl, R., Jones, B., … Wilson, A. G. (2012a). Statistical engineering – Forming the foundations. Quality Engineering, 24, 110–132.10.1080/08982112.2012.641150
  • Anderson-Cook, C. M., Lu, L., Clark, G., DeHart, S. P., Hoerl, R., Jones, B., … Wilson, A. G. (2012b). Statistical engineering – Roles for statisticians and the path forward. Quality Engineering, 24, 110–132.10.1080/08982112.2012.641150
  • Antony, J., Bhuller, A. S., Kumar, M., Mendibil, K., & Montgomery, D. C. (2012). Application of Six Sigma DMAIC methodology in a transactional environment. International Journal of Quality and Reliability Management, 29, 31–53.10.1108/02656711211190864
  • Borror, C. M., Beechy, T., Shunk, D., Gish, M., & Montgomery, D. C. (2011). TASER’s roadmap to quality. The Quality Management Forum, 37, 13–18.
  • Duarte, B., Montgomery, D. C., Fowler, J., & Konopka, J. (2012). Deploying LSS in a global enterprise – Project identification. International Journal of Lean Six Sigma, 3, 187–205.10.1108/20401461211282709
  • Harry, M., & Schroeder, R. (2000). Six Sigma: The breakthrough management strategy revolutionizing the world’s top corporations. New York, NY: Random House.
  • Kumar, M., Antony, J., Madu, C. N., Montgomery, D. C., & Park, S. H. (2008). Common myths of Six Sigma demystified. International Journal of Quality & Reliability Management, 25, 878–895.10.1108/02656710810898658
  • Montgomery, D. C. (1999). “experimental design for product and process design and development” (with commentary). Journal of the Royal Statistical Society Series D (The Statistician), 48, 159–177.
  • Montgomery, D. C. (2004a). Improving business performance: Project-by-project. Editorial in Quality and Reliability Engineering International (Vol. 20, p. iii).
  • Montgomery, D. C. (2004b). Selecting the right improvement projects. Editorial in Quality and Reliability Engineering International (Vol. 20, pp. iii–iv).
  • Montgomery, D. C. (2008). Does Six Sigma stifle innovation? Editorial in Quality and Reliability Engineering International (Vol. 24, p. 249).10.1002/(ISSN)1099-1638
  • Montgomery, D. C. (2011). Innovation and quality technology. Editorial in Quality and Reliability Engineering International (Vol. 27, pp. 733–734).
  • Montgomery, D. C. (2012). Design and analysis of experiments (8th ed.). Hoboken, NJ: Wiley.
  • Montgomery, D. C. (2013). Introduction to statistical quality control (7th ed.). Hoboken, NJ: Wiley.
  • Montgomery, D. C., & Woodall, W. H. (2008). An overview of Six Sigma. International Statistical Review, 76, 329–346.10.1111/insr.2008.76.issue-3
  • Montgomery, D. C., Jennings, C. L., & Pfund, M. E. (2011). Managing, controlling and improving quality. Hoboken, NJ: Wiley.
  • Noorossana, R., Saghaei, A., & Amari, A. (2011). Statistical analysis of profile monitoring. Hoboken, NJ: Wiley.10.1002/9781118071984
  • Steinberg, D. M., Bisgaard, S., Doganaksoy, N., Fisher, N., Gunter, B., Hahn, G., … Wu, C. F. J. (2008). The future of industrial statistics: A panel discussion. Technometrics, 50, 103–127.
  • Woodall, W. H., & Montgomery, D. C. (1999). Research issues and ideas in statistical process control. Journal of Quality Technology, 31, 376–386.
  • Woodall, W. H., & Montgomery, D. C. (2014). Some current trends in the theory and application of statistical process monitoring. Journal of Quality Technology, 46, 78–94.

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