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Quality control

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INTRODUCTION

While interest in quality is as old as industry itself, quality control as a technical and managerial discipline started to become accepted and widely practiced only in the 1940s and 1950s. Statistical methods of quality control, though developed in the United States and Britain, found their most ardent followers among Japanese businessmen and managers in the post-War decades. Statistical quality control (SQC) consultants such as W.E. Deming became household names in Japan while they were scarcely known in their own countries. During the decade of the 1980s, however, there was a renewed interest in quality control in the West, spurred no doubt by the globalization of competition and increasing customer awareness of quality. The Malcolm Baldridge (MB) Award is one continuous improvement program that has had a great impact on putting quality on top managements’ agendas throughout the nation. Even those companies that do not apply for the award are using the MB criteria to...

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References

  1. Alt, F.B., Deutsch, S.J., and Walker, J.W. (1997). “Control Charts for Multivariate, Correlated Observations,” ASQC Quality Congress Transactions, Philadelphia, 360–369.

    Google Scholar 

  2. Anin, R.W. and Ethridge, R.A. (1998). “A Note on Individual and Moving Range Control Charts,” Jl. Quality Technology, 30, 70–74.

    Google Scholar 

  3. ASQC (1983). Glossary and Tables for Statistical Quality Control, 2nd ed., American Society for Quality Control, Milwaukee, Wisconsin.

    Google Scholar 

  4. Atienza, O.O., Tang, L.C., and Ang, B.W. (1988). “A SPC Procedure for Detecting Level Shifts of Autocorrelated Processes,” Jl. Quality Technology, 30, 340–351.

    Google Scholar 

  5. Bai, D.S. and Choi, I.S. (1995). “ and R Control Charts for Skewed Populations,” Jl. Quality Technology, 27, 120–131.

    Google Scholar 

  6. Bendell, A., Disney, J., and Pridmore,W.A., eds. (1989). Taguchi Methods: Applications in World Industry. Springer-Verlag, New York.

    Google Scholar 

  7. Blakeslee, J.A. (1999). “Implementing the Six Sigma Solution,” Quality Progress, 32, 77–85.

    Google Scholar 

  8. Borror, C.M., Champ, C.W., and Rigdon, S.R. (1998). “Poisson EWMA Control Charts,” Jl. Quality Technology, 30, 352–361.

    Google Scholar 

  9. Borror, C.M., Montgomery, D.C., and Runger, G.C. (1999). “Robustness of the EWMA Control Chart to Non-normality,” Jl. Quality Technology, 31, 309–316.

    Google Scholar 

  10. Box, G. and Luceñ O. A. (1997). Statistical Control by Monitoring and Feedback Adjustment, John Wiley, New York.

    Google Scholar 

  11. Box, G.E.P. (1957). “Evolutionary Operation: A Method of Increasing Industrial Productivity,” Applied Statistics, 6(2), 81–101.

    Google Scholar 

  12. Brook, D. and Evans, D.A. (1972). “An Approach to the Probability Distribution of Cusum Run Length,” Biometrica, 59, 539–549.

    Google Scholar 

  13. Chang, T.C. and Gan, F.F. (1995). “A Cumulative Sum Control Chart for Monitoring Process Variance,” Jl. Quality Technology, 27, 109–119.

    Google Scholar 

  14. Crosier, R.B. (1986). “A New Two-Sided Cumulative Sum Quality Control Scheme,” Technometrics, 28, 187–194.

    Google Scholar 

  15. Crowder, S.V. (1987). “Computation of ARL for Combined Individual Measurement and Moving Range Charts,” Jl. Quality Technology, 19, 98–102.

    Google Scholar 

  16. Crowder, S.V. (1987). “A Simple Method for Studying Run Length Distributions of Exponentially Weighted Moving Average Charts,” Technometrics, 29, 401–407.

    Google Scholar 

  17. Crowder, S.V. (1989). “Design of Exponentially Weighted Moving Average Schemes,” Jl. Quality Technology, 21, 155–162.

    Google Scholar 

  18. Crowder, S.V. and Hamilton, M. (1992). “An EWMA for Monitoring a Process Standard Deviation,” Jl. Quality Technology, 24, 12–21.

    Google Scholar 

  19. Dehnad, K., ed. (1989). Quality Control, Robust Design, and the Taguchi Method. Wadsworth and Brooks, Pacific Grove, California.

    Google Scholar 

  20. Deming, W.E. (1986). Out of the Crisis. MIT Press, Cambridge, Massachusetts.

    Google Scholar 

  21. Duncan, A.J. (1986). Quality Control and Industrial Statistics, 5th ed., Irwin, Homewood, Illinois.

    Google Scholar 

  22. Gan, F.F. (1991). “An Optimal Design of CUSUM Quality Control Charts,” Jl. Quality Technology, 23, 279–286.

    Google Scholar 

  23. Gan, F.F. (1993). “An Optimal Design of CUSUM Control Charts for Binomial Counts,” Jl. Applied Statistics, 20, 445–460.

    Google Scholar 

  24. Gan, F.F. (1998). “Design of One- and Two-Sided Exponential EWMA Charts,” Jl. Quality Technology, 30, 55–69.

    Google Scholar 

  25. Gibra, I.N. (1975). “Recent Developments in Control Chart Techniques,” Jl. Quality Technology, 7, 183–192.

    Google Scholar 

  26. Gitlow, H., Oppenheim, A., and Oppenheim, R. (1995). Quality Management: Tools and Methods for Improvement, 2nd ed., Irwin, Homewood, Illinois.

    Google Scholar 

  27. Goel, A.L. and Wu, S.M. (1971). “Determination of ARL and a Contour Nomogram for Cusum Charts to Control Normal Mean,” Technometrics, 13, 221–230.

    Google Scholar 

  28. Goel, A.L. (1981). “Cumulative Sum Control Charts,” In S. Kotz and N.L. Johnson, eds., Encyclopedia of Statistical Sciences. John Wiley, New York.

    Google Scholar 

  29. Goldsmith, P.L. and Whitfield, H. (1961). “Average Run Length Cumulative Chart Control Schemes,” Technometrics, 3, 11–20.

    Google Scholar 

  30. Grant, E.L. and Leavenworth, R.S. (1988). Statistical Quality Control, 6th ed., McGraw-Hill, New York.

    Google Scholar 

  31. Hawkins, D.M. (1981). “A CUSUM for a Scale Parameter,” Jl. Quality Technology, 13, 228–231.

    Google Scholar 

  32. Hawkins, D.M. (1992). “A Fast, Accurate Approximation of Average Run Lengths of CUSUM Control Charts,” Jl. Quality Technology, 24, 37–43.

    Google Scholar 

  33. Hawkins, D.M. (1993). “Cumulative Sum Control Charting: An Underutilized SPC Tool,” Quality Engineering, 5, 463–477.

    Google Scholar 

  34. Hsiang, T. and Taguchi, G. (1985). Paper presented at the Annual Meeting of the American Statistical Association, Las Vegas, Nevada.

    Google Scholar 

  35. Hunter, J.S. (1986). “The Exponentially Weighted Moving Average,” Jl. Quality Technology, 18, 203–210.

    Google Scholar 

  36. Johnson, N.L. and Leone, F.C. (1962). “Cumulative Sum Control Charts — Mathematical Principles Applied to Their Construction and Use”, Part I, II, & III. Industrial Quality Control, June, 15–21; July, 29–36; and August, 22–28.

    Google Scholar 

  37. Joseph, J. and Bowen, V. (1991). “A Cumulative Bayesian Technique for Use in Quality Control Schemes,” Proceedings of the American Statistical Association, Alexandria, Virginia.

    Google Scholar 

  38. Kemp, K.W. (1961). “The Average Run Length of the Cumulative Sum Chart When a V-Mask is Used,” Jl. Royal Statistical Society, Series B, 23, 149–153.

    Google Scholar 

  39. Khan, R.A. (1978). “Wald’s Approximations to the Average Run Length in Cusum Procedures,” Jl. Statistical Planning and Inference, 2, 63–77.

    Google Scholar 

  40. Kotz, S. and Johnson, N.L. (1993). Process Capability Indices, Chapman-Hall, London.

    Google Scholar 

  41. Levine, D.M., Ramsey, P.R., and Berenson, M.L. (1995). Business Statistics for Quality and Productivity, Prentice-Hall, Englewood Cliffs, New Jersey.

    Google Scholar 

  42. Lowry, C.A., Champ, C.W., and Woodall, W.H. (1995). “Performance of Control Charts for Monitoring Process Variation,” Communications in Statistics — Simulation and Computation, 24, 409–437.

    Google Scholar 

  43. Lu, C.-W. and Reynolds, M.R. (1999). “EWMA Control Charts for Monitoring the Mean of Autocorrelated Process,” Jl. Quality Technology, 31, 166–188.

    Google Scholar 

  44. Lu, C.-W. and Reynolds, M.R. (1999). “Control Charts for Monitoring the Mean and Variance of Autocorrelated Processes,” Jl. Quality Technology, 31, 259–274.

    Google Scholar 

  45. Lucas, J.M. (1982). “Combined Shewhart-Cusum Quality Control Schemes,” Jl. Quality Technology, 14, 51–59.

    Google Scholar 

  46. Lucas, J.M. (1985). “Counted Data CUSUM’s,” Technometrics, 27, 129–144.

    Google Scholar 

  47. Lucas, J.M. and Crosier, R.B. (1982). “Fast Initial Response for Cusum Quality Control Schemes,” Technometrics, 24, 199–205.

    Google Scholar 

  48. Lucas, J.M. and Saccucci, M.S. (1990). “Exponentially Weighted Moving Average Control Schemes, Properties and Enhancements,” Technometrics, 32, 1–12.

    Google Scholar 

  49. MacGregor, J.F. and Harris, T.J. (1993). “The Exponentially Weighted Moving Variance,” Jl. Quality Technology, 25, 106–118.

    Google Scholar 

  50. McCabe, W. (1985). “Improving Quality and Cutting Costs in a Service Organization,” Quality Progress, 18, 85–89.

    Google Scholar 

  51. Mitra, A. (1998). Fundamentals of Quality Control and Improvement, 2nd ed., Prentice-Hall, Englewood Cliffs, New Jersey.

    Google Scholar 

  52. Montgomery, D.C. (1997). Introduction to Statistical Quality Control, 3rd ed., John Wiley, New York.

    Google Scholar 

  53. Montgomery, D.C. (1997). Design and Analysis of Experiments, 4th ed., John Wiley, New York.

    Google Scholar 

  54. Myers, R.H. and Montgomery, D.C. (1995). Response Surface Methodology: Process and Product Optimization Using Designed Experiments, John Wiley, New York.

    Google Scholar 

  55. Nelson, L.S. (1984). “The Shewhart Control Chart — Tests for Special Cases,” Jl. Quality Technology, 16, 237–239.

    Google Scholar 

  56. Nelson, L.S. (1985). “Interpreting Shewhart Control Charts,” Jl. Quality Technology, 17, 114–116.

    Google Scholar 

  57. Page, E.S. (1954). “Continuous Inspection Schemes,” Biometrika, 41, 100–115.

    Google Scholar 

  58. Page, E.S. (1961). “Cumulative Sum Charts,” Technometrics, 3, 1–9.

    Google Scholar 

  59. Page, E.S. (1963). “Controlling the Standard Deviation by Cusums and Warning Lines,” Technometrics, 5.

    Google Scholar 

  60. Palm, A.C. (1990). “Tables of Run Length Percentiles for Determining the Sensitivity of Shewhart Control Charts for Averages with Supplementary Runs Rules,” Jl. Quality Technology, 22, 289–298.

    Google Scholar 

  61. Pignatiello, J.J., Jr. and Ramberg, J.S. (1993). “Process Capability Indices: Just Say No!” ASQC Annual Technical Conference Proceedings, 92–104.

    Google Scholar 

  62. Pollack, M. and Siegmund, D. (1986). Approximations to the Average Run Length of Cusum Tests. Technical Report 37, Department of Statistics, Stanford University, California.

    Google Scholar 

  63. Ramberg (1999). “Total Quality Management.” In Gass, S.I. and C.M. Harris, eds., Encyclopedia of Operations Research and Management Science. Kluwer Academic Publishers, Norwell, Massachusetts.

    Google Scholar 

  64. Reynolds, M.R., Jr. (1975). “Approximations to the Average Run Length in Cumulative Sum Control Charts,” Technometrics, 17, 65–71.

    Google Scholar 

  65. Reynolds, Jr. M.R. and Stoumbos, Z.G. (1999). “A CUSUM Chart for Monitoring a Proportion when Inspecting Continuously,” Jl. Quality Technology, 31, 87–108.

    Google Scholar 

  66. Roberts, S.W. (1959). “Control Chart Tests Based on Geometric Moving Averages,” Technometrics, 1, 239–250.

    Google Scholar 

  67. Roberts, H.V. and Sergesketter, B.E. (1993). Quality is Personal, A Foundation for Total Quality Management. Free Press, New York.

    Google Scholar 

  68. Rosander, A.C. (1991). Deming’s 14 Points Applied to Services, Marcel Dekker, New York.

    Google Scholar 

  69. Runger, G.C., Willemain, T.R., and Prabhu, S. (1995). “Average Run Lengths for SUSUM Control Charts Applied to Residuals,” Communications in Statistics — Theory and Methods, 24, 273–282.

    Google Scholar 

  70. Ryan, T.R. (1989). Statistical Methods for Quality Improvement. John Wiley, New York.

    Google Scholar 

  71. Schilling, E.G. (1982). Acceptance Sampling in Quality Control, Marcel Dekker, New York.

    Google Scholar 

  72. Schilling, E.G. and Nelson, P.R. (1976). “The Effect of Non-Normality on the Control Limits of Charts,” Jl. Quality Technology, 8, 183–188.

    Google Scholar 

  73. Shewhart, W.A. (1931). Economic Control of Quality of Manufactured Product. Van Nostrand, New York.

    Google Scholar 

  74. Taguchi, G. (1976). Experimental Design, Vol. 1, 3rd ed., Maruzen, Tokyo.

    Google Scholar 

  75. Taguchi, G. (1977). Experimental Design, Vol. 2, 3rd ed., Maruzen, Tokyo.

    Google Scholar 

  76. Taguchi, G. and Wu, Y. (1979). Introduction to Off-line Quality Control. Central Japan Quality Control Association, Nagoya.

    Google Scholar 

  77. Taylor, W.A. (1992). Guide to Acceptance Sampling, Taylor Enterprises Inc., Lake Villa, Illinois.

    Google Scholar 

  78. Van Brackle, L.N. and Reynolds, M.R., Jr. (1997). “EWMA and CUSUM Control Charts in the Presence of Correlation,” Communications in Statistics — Simulation and Computation, 26, 979–1008.

    Google Scholar 

  79. Vance, L.C. (1983). “A Bibliography of Statistical Quality Control chart Techniques, 1970–1980,” Jl. Quality Technology, 15, 59–62.

    Google Scholar 

  80. Vance, L.C. (1986). “Average Run Lengths of Cumulative Sum Control Charts for Controlling Normal Means,” Jl. Quality Technology, 18, 189–193.

    Google Scholar 

  81. Vardeman, S.B. and Jobe, J.M. (1999). Statistical Quality Assurance Methods for Engineers, John Wiley, New York.

    Google Scholar 

  82. Wald, A. (1947). Sequential Analysis. John Wiley, New York.

    Google Scholar 

  83. Waldman, K.H. (1986). “Bounds for the Distribution of the Run Length of One-Sided and Two-Sided CUSUM Quality Control Schemes,” Technometrics, 28, 61–67.

    Google Scholar 

  84. Western Electric Co. (1956). Statistical Quality Control Handbook, Western Electric Corporation, Indianapolis, Indiana.

    Google Scholar 

  85. Woodall, W.H. (1983). “The Distribution of the Run Length of One-Sided Cusum Procedures for Continuous Random Variables,” Technometrics, 25, 295–301.

    Google Scholar 

  86. Woodall, W.H. (1984). “On the Markov Chain Approach to the Two-Sided Cusum Procedure,” Technometrics, 26, 41–46.

    Google Scholar 

  87. Woodall, W.H. (1986). “The Design of CUSUM Quality Control Charts,” Jl. Quality Technology, 18, 99–102.

    Google Scholar 

  88. Woodall, W.H. (1997). “Control Charting Based on Attribute Data: Bibliography and Review,” Jl. Quality Technology, 29, 172–183.

    Google Scholar 

  89. Woodall, W.H. and Adams, B.M. (1993). “The Statistical Design of CUSUM Charts,” Quality Engineering, 5, 559–570.

    Google Scholar 

  90. Zacks, S. (1981). “The Probability Distribution and the Expected Value of a Stopping Variable Associated with One-Sided Cusum Procedures for Non-Negative Integer Valued Random Variables,” Communications in Statistics–Theory and Methods, A10, 2245–2258.

    Google Scholar 

  91. Zuckerman, A. (1999). “ISO 9000 Revisions are Key to Knowledge Age Excellence,” Quality Progress, 32, 35–39.

    Google Scholar 

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© 2001 Kluwer Academic Publishers

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Alt, F., Jain, K. (2001). Quality control . In: Gass, S.I., Harris, C.M. (eds) Encyclopedia of Operations Research and Management Science. Springer, New York, NY. https://doi.org/10.1007/1-4020-0611-X_840

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  • DOI: https://doi.org/10.1007/1-4020-0611-X_840

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