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Monitoring linear profiles using an adaptive control chart

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Abstract

We propose a model for the statistical design of a variable sample size chi-squared control chart (VSS χ 2 control chart) for monitoring linear profiles. Performance measures of the proposed adaptive control chart are obtained through a Markov chain approach. Through a numerical example, which consists of a calibration application in a production process of semiconductors, the proposed chart is compared to the fixed parameter chi-squared control chart (FP χ 2 chart) to monitor the intercept and slope of the linear profile. From this example, it is possible to assess the potential benefits provided by the proposed chart. Also, considering simultaneous shifts in the intercept, the slope, and the standard deviation, a sensitivity analysis of the proposed chart for monitoring linear profiles is presented.

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References

  1. Amin RW, Miller RW (1993) A robustness study of \( \overline{X} \) charts with variable sampling intervals. J Qual Technol 25:35–44

    Google Scholar 

  2. Aparisi F (1996) Hotelling’s T 2 control chart with adaptive sample sizes. Int J Prod Res 34:2835–2862

    Article  MATH  Google Scholar 

  3. Aparisi F, Haro CL (2001) Hotelling’s T 2 control chart with sampling intervals. Int J Prod Res 39:3127–3140

    Article  MATH  Google Scholar 

  4. Aparisi F, Haro CL (2003) A comparison of T 2 control charts with variable sampling schemes as opposed to NEWMA chart. Int J Prod Res 41:2169–2182

    Article  Google Scholar 

  5. Bersimis S, Psarakis S, Panaretos J (2007) Multivariate statistical process control charts: an overview. Qual Reliab Eng Int 23:517–543

    Article  Google Scholar 

  6. Costa AFB (1994) \( \overline{X} \) charts with variable sampling size. J Qual Technol 26:155–163

    Google Scholar 

  7. Costa AFB (1999) Joint \( \overline{X} \) and R charts with variable sample sizes and sampling intervals. J Qual Technol 31:387–397

    Google Scholar 

  8. Costa AFB, Machado MAG (2011) Variable parameter and double sampling \( \overline{X} \) charts in the presence of correlation: the Markov chain approach. Int J Prod Econ 130:224–229

    Article  Google Scholar 

  9. De Magalhães MS, Costa AFB, Epprecht EK (2002) Constrained optimization model for the design of an adaptive \( \overline{X} \) chart. Int J Prod Res 40:3199–3218

    Article  MATH  Google Scholar 

  10. De Magalhães MS, Costa AFB, Moura Neto FD (2009) A hierarchy of adaptative \( \overline{X} \) control charts. Int J Prod Econ 119:271–283

    Article  Google Scholar 

  11. Faraz A, Heuchenne C, Saniga E, Costa AFB (2014) Double objective economic statistical design of the VPT2 control chart: Wald’s identity approach. J Stat Comput Simul 84:2123–2137

    Article  MathSciNet  Google Scholar 

  12. Kang L, Albin SL (2000) On-line monitoring when the process yields a linear profile. J Qual Technol 32:418–426

    Google Scholar 

  13. Kim K, Mahmoud M, Woodall WH (2003) On the monitoring of linear profiles. J Qual Technol 35:317–328

    Google Scholar 

  14. Mahmoud MA, Woodall WH (2004) Phase I analysis of linear profiles with calibration applications. Technometrics 46:380–391

    Article  MathSciNet  Google Scholar 

  15. Mahmoud MA, Morgan JP, Woodall WH (2010) The monitoring of simple linear regression profiles with two observations per sample. J Appl Stat 37:1249–1263

    Article  MathSciNet  Google Scholar 

  16. Mahmoud MA (2012) The performance of phase II simple linear profile approaches when parameters are estimated. Commun Stat Simul Comput 41:1816–1833

    Article  MathSciNet  MATH  Google Scholar 

  17. Moura Neto FD, De Magalhães MS (2012) A laplacian spectral method in phase I analysis of profiles. Appl Stoch Model Bus Ind 28:251–263

    Article  MathSciNet  Google Scholar 

  18. Nenes G (2011) A new approach for the economic design of fully adaptive control charts. Int J Prod Econ 131:631–642

    Article  Google Scholar 

  19. Prabhu SS, Runger GC, Keats JB (1993) \( \overline{X} \) chart with adaptive sample sizes. Int J Prod Res 31:2895–2909

    Article  Google Scholar 

  20. Prabhu SS, Montgomery DC, Runger GC (1997) Economic-statistical design of an adaptive \( \overline{X} \) chart. Int J Prod Econ 49:1–15

    Article  Google Scholar 

  21. Park C, Reynolds MR Jr (1999) Economic design of a variable sampling rate \( \overline{X} \) chart. J Qual Technol 31:427–443

    Google Scholar 

  22. Reynolds MR Jr et al (1988) \( \overline{X} \) charts with variable sampling intervals. Technometrics 30:181–192

    MathSciNet  Google Scholar 

  23. Reynolds MR Jr, Cho GY (2011) Multivariate monitoring of the process mean and variability with variable sampling intervals. Seq Anal 30:1–40

    Article  MathSciNet  MATH  Google Scholar 

  24. Runger GC, Prabhu SS (1996) A Markov chain model for the multivariate exponentially weighted moving averages control chart. J Am Stat Assoc 91:1701–1706

    Article  MathSciNet  MATH  Google Scholar 

  25. Staudhammer C, Maness TC, Kozac RA (2007) Profile charts for monitoring lumber manufacturing using laser range sensor data. J Qual Technol 39:224–240

    Google Scholar 

  26. Stover FS, Brill RV (1998) Statistical quality control applied to ion chromatography calibrations. J Chromatogr A 804:37–43

    Article  Google Scholar 

  27. Woodall WH, Ncube MM (1985) Multivariate CUSUM quality-control procedures. Technometrics 27:285–292

    Article  MathSciNet  MATH  Google Scholar 

  28. Zhang H, Albin S (2009) Detecting outliers in complex profiles using a χ 2 control chart method. lIE Trans 41:335–345

    Google Scholar 

  29. Zhang G, Shing I (2008) Multivariate EWMA control charts using individual observations for process mean and variance monitoring and diagnosis. Int J Prod Res 46:6855–6881

    Article  Google Scholar 

  30. Zhang J, Li Z, Wang Z (2012) A new adaptive control chart for monitoring process mean and variability. Int J Adv Manuf Technol 60:1031–1038

    Article  Google Scholar 

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Correspondence to Maysa S. De Magalhães.

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De Magalhães, M.S., Von Doellinger, R.O.S. Monitoring linear profiles using an adaptive control chart. Int J Adv Manuf Technol 82, 1433–1445 (2016). https://doi.org/10.1007/s00170-015-7429-z

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  • DOI: https://doi.org/10.1007/s00170-015-7429-z

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