Acknowledgement
Supported by : Kyung Hee University
References
- Adams, B. M. and Tseng, I. T. (1998), Robustness of Forecast-Based Monitoring Schemes, Journal of Quality Technology, 30(4), 328-339 https://doi.org/10.1080/00224065.1998.11979869
- Alwan, L. C. (1992), Effects of Autocorrelation on Control Chart Performance, Communications in Statistics: Theory and Method, 21(4), 1025-1049 https://doi.org/10.1080/03610929208830829
- Alwan, L. C. and Roberts, H. V. (1988), Time-Series Modeling for Statistical Process Control, Journal of Business & Economic Statistics, 6(1), 87-95 https://doi.org/10.2307/1391421
- Apley, D.W. (2002), Time Series Control Charts in the Presence of Model Uncertainty, ASME Journal of Manufacturing Science and Engineering, 124(4), 891-898 https://doi.org/10.1115/1.1510520
- Apley, D. W. and Chin, C. (2007), An Optimal Filter Design Approach to Statistical Process Control, Journal of Quality Technology, 39(2), 93-117 https://doi.org/10.1080/00224065.2007.11917678
- Apley, D. W. and Lee, H. C. (2003), Design of Exponentially WeightedMoving Average Control Charts for Autocorrelated Processes with Model Uncertainty, Technometrics, 45(3), 187-198 https://doi.org/10.1198/004017003000000014
- Apley, D.W. and Lee, H. C. (2008), Robustness Comparison of Exponentially Weighted Moving Average Charts on Autocorrelated Data and on Residuals, Journal of Quality Technology, to appear
- Apley, D. W. and Shi, J. (1999), GLRT for Statistical Process Control of Autocorrelated Processes, IIE Transactions, 31(12), 1123-1134
- Bagshaw, M. and Johnson, R. A. (1975), The Effect of Serial Correlation on the Performance of CUSUM Tests II, Technometrics, 17(1), 73-80 https://doi.org/10.2307/1268003
- Bagshaw, M. and Johnson R. A. (1977), Sequential Procedures for Detecting Parameter Changes in a Time-Series Model, Journal of the American Statistical Association, 72(359), 593-597 https://doi.org/10.2307/2286222
- Berthouex, P. M., Hunter, E. and Pallesen, L. (1978), Monitoring Sewage Treatment Plants: SomeQuality Control Aspects, Journal of Quality Technology, 10(4), 139-149 https://doi.org/10.1080/00224065.1978.11980842
- Box, G. E. P., Jenkins, G., and Reinsel, G. (1994), Time Series Analysis, Forecasting, and Control, 3rd ed., Prentice-Hall, Englewood Cliffs, NJ
- Box, G. E. P. and Ramírez, J. (1992), Cumulative Score Charts, Quality and Reliability Engineering International, 8(1), 1727
- Box, G. E. P. and Luceño, A. (1997), Statistical Control by Monitoring and Feedback Adjustment, Wiley, New York, NY
- Chin, C. (2008), Modified Cuscore Charts for Autocorrelated Processes, to be submitted
- Chin, C. and Apley, D. W. (2006), Optimal Design of Second- Order Linear Filters for Control Charting. Technometrics, 48(3) 337-348 https://doi.org/10.1198/004017006000000020
- English, J. R., Lee, S-c.,Martin, T. W., and Tilmon, C. (2000), Detecting Changes in Autoregressive Processes with X-bar and EWMA charts, IIE Transactions, 32(12) 1103-1113
- Fisher, R. A. (1925), Theory of Statistical Estimation, Proceeding of the Cambridge Philosophical Society, 22, 700-725
- Goldsmith, P. L. and Whitefield, H. (1961), Average Run Lengths in Cumulative Chart Quality Control Schemes, Technometrics, 3(1), 11-20 https://doi.org/10.2307/1266473
- Harris, T. J. and Ross,W. H. (1991), Statistical Process Control Procedures for Correlated Observations, Canadian Journal of Chemical Engineering, 69, 48-57 https://doi.org/10.1002/cjce.5450690106
- Hunter, J. S. (1986), The Exponentially Weighted Moving Average, Journal of Quality Technology, 18(4), 203-210 https://doi.org/10.1080/00224065.1986.11979014
- Jiang W. and Tsui, K. (2001), Some Properties of the ARMA Control Chart, Nonlinear Analysis, 47, 2073-2088 https://doi.org/10.1016/S0362-546X(01)00334-0
- Jiang, W., Tsui, K. and Woodall, W. H. (2000), A New SPC Monitoring Method: The ARMA Chart, Technometrics, 42 (4), 399-410 https://doi.org/10.2307/1270950
- Johnson, R. A. and Bagshaw, M. (1974), The Effect of Serial Correlation on the Performance of CUSUM Tests, Technometrics, 16(1), 103-112 https://doi.org/10.2307/1267498
- Lin, S.W., and Adams, B.M. (1996), Combined Control Charts for Forecast-Based Monitoring Schemes, Journal of Quality Technology, 28(3), 289-301 https://doi.org/10.1080/00224065.1996.11979679
- Luceno, A. (1999), Average Run Lengths and Run Length Probability Distributions for Cuscore Charts to Control Normal Mean, Computational Statistics and Data Analysis, 32(2), 177-195 https://doi.org/10.1016/S0167-9473(99)00025-0
- Lu, C. and Reynolds, M. R., Jr. (1999a), EWMA Control Charts forMonitoring theMean ofAutocorrelated Processes, Journal of Quality Technology, 31(2), 166-188 https://doi.org/10.1080/00224065.1999.11979913
- Lu, C. and Reynolds, M. R., Jr. (1999b), Control Charts for Monitoring the Mean and Variance of Autocorrelated Processes. Journal of Quality Technology, 31(3), 259-274 https://doi.org/10.1080/00224065.1999.11979925
- Lucas, J.M. and Saccucci,M. S. (1990), ExponentiallyWeighted Moving Average Control Schemes: Properties and Enhancements, Technometrics, 32(1), 1-12 https://doi.org/10.2307/1269835
- Luceno, A. (2004), Cuscore Charts to Detect Level Shifts in Autocorrelated Noise, Quality Technology and Quantitative Management, 1(1), 27-45 https://doi.org/10.1080/16843703.2004.11673063
- Montgomery, D. C. (2005), Introduction to Statistical Quality Control, 5th ed.,Wiley, New York, NY
- Montgomery, D. C. and Mastrangelo, C. M. (1991), Some Statistical Process Control Methods for Autocorrelated Data, Journal of Quality Technology, 23(3), 179-193 https://doi.org/10.1080/00224065.1991.11979321
- Montgomery, D. C. andWoodall,W. H. (1997), ADiscussion of Statistically-Based Process Monitoring and Control, Journal of Quality Technology, 29(2), 121-162 https://doi.org/10.1080/00224065.1997.11979738
- Moustakides, G. (1986), Optimal Stopping Times for Detecting Changes in Distributions. Annals of Statistics, 14(4), 1379- 1387 https://doi.org/10.1214/aos/1176350164
- Page, E. S. (1955),ATest for a Change in a ParameterOccurring at an Unknown Point, Biometrica, 42(3/4), 523-527 https://doi.org/10.1093/biomet/42.3-4.523
- Pandit, S. M., and Wu, S. M. (1983), Time Series and System Analysis, With Applications, New York: JohnWiley
- Reynolds, M. R., Jr., and Stoumbos, Z. (2001), Monitoring the Process Mean and Variance Using Individual Observations and Variable Sampling Intervals, Journal of Quality Technology, 33(2), 181-205 https://doi.org/10.1080/00224065.2001.11980066
- Roberts, S. W. (1959),Control Chart Tests Based on Geometric Moving Averages, Technometrics, 1(3), 239-250 https://doi.org/10.2307/1266443
- Runger,G. C. and Testik,M. C. (2003), Control Charts forMonitoring Fault Signatures: Cuscore versus GLR, Quality and Reliability Engineering International 19, 387-396 https://doi.org/10.1002/qre.591
- Runger, G. C.,Willemain, T. R., and Prabhu, S. (1995), Average Run Lengths for CUSUM Control Charts Applied to Residuals, Communications in Statistics - Theory and Methods, 24(1), 273-282 https://doi.org/10.1080/03610929508831487
- Shu, L., Apley, D. W., and Tsung, F. (2002), Autocorrelated ProcessMonitoring Using Triggered Cuscore Charts, Quality and Reliability Engineering International, 18, 411-421 https://doi.org/10.1002/qre.492
- Stoumbos, Z. G., Reynolds,M. R., Ryan, T. P., andWoodall,W. H. (2000), The State of Statistical Process Control as We Proceed into the 21st Century, Journal of the American Statistical Association, 95(451), 992-998 https://doi.org/10.2307/2669484
- Superville, C. R. and Adams, B. M. (1994), An Evaluation of Forecast-BasedQualityControl Schemes, Communications in Statistics: Simulation and Computation, 23(3), 645-661 https://doi.org/10.1080/03610919408813191
- VanBrackle, 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(3), 979-1008 https://doi.org/10.1080/03610919708813421
- Vander Wiel, S. A. (1996), Monitoring Processes That Wander Using Integrated Moving Average Models, Technometrics, 38(2), 139-151 https://doi.org/10.2307/1270407
- Vasilopoulos, A. V. and Stamboulis, A. P. (1978), Modification of Control Chart Limits in the Presence of Data Correlation, Journal of Quality Technology, 10(1), 20-30 https://doi.org/10.1080/00224065.1978.11980809
- Wardell,D.G.,Moskowitz,H., and Plante, R.D. (1992), Control Charts In the Presence of Data Correlation, Management Science, 38(8), 1084-1105 https://doi.org/10.1287/mnsc.38.8.1084
- Wardell, D. G., Moskowitz, H., and Plante, R. D. (1994), Run-LengthDistributions of Special-CauseControl Charts for Correlated Observations, Technometrics, 36(1), 3-27 https://doi.org/10.2307/1269191
- Woodall, W. H. and Faltin, F. (1993), Autocorrelated Data and SPC, ASQC Statistics Division Newsletter, 13(4), 1821
- Woodall,W. H. andMontgomery, D. C. (1999), Research Issues and Ideas in Statistical Process Control, Journal of Quality Technology, 31(4), 376-386 https://doi.org/10.1080/00224065.1999.11979944
- Yang J. and Makis V. (1997), On the Performance of Classical Control Charts Applied to Process Residuals, Computers and Industrial Engineering, 33, 121-124 https://doi.org/10.1016/S0360-8352(97)00055-7
- Yashchin, E. (1993), Performance of CUSUMControl Schemes for Serially Correlated Observation, Technometrics, 35(1), 37-52 https://doi.org/10.2307/1269288
- Zhang, N. F. (1998), A Statistical Control Chart for Stationary Process Data, Technometrics, 40(1), 24-38 https://doi.org/10.2307/1271390