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Generalized Q Control Charts for Short Run Processes in the Presence of Lot to Lot Variability

Lot간 변동이 존재하는 Short Run 공정 적용을 위한 일반화된 Q 관리도

  • Lee, Hyun Cheol (Korea Aerospace University, Department of Business Administration)
  • 이현철 (한국항공대학교 경영학과)
  • Received : 2014.06.03
  • Accepted : 2014.08.11
  • Published : 2014.11.30

Abstract

We derive a generalized statistic form of Q control chart, which is especially suitable for short run productions and start-up processes, for the detection of process mean shifts. The generalization means that the derived control chart statistic concurrently uses within lot variability and between lot variability to explain the process variability. The latter variability source is noticeably prevalent in lot type production processes including semiconductor wafer fabrications. We first obtain the generalized Q control chart statistic when both the process mean and process variance are unknown, which represents the case of implementing statistical process control charting for short run productions and start-up processes. Also, we provide the corresponding generalized Q control chart statistics for the rest of three cases of previous Q control chart statistics : (1) both the process mean and process variance are known (2) only the process mean is unknown and (3) only the process variance is unknown.

Keywords

References

  1. 이현철, "검출력 향상된 자기상관 공정용 관리도의 강건 설계:반도체 공정설비 센서데이터 응용", 산업경영시스템학회지, 제34권, 제4호(2011), pp.57-65.
  2. Apley, D.W. and H.C. Lee, "Design of Exponentially Weighted Moving Average Control Charts for Autocorrelated Processes With Model Uncertainty," Technometrics, Vol.45, No.3(2003), pp.187-198. https://doi.org/10.1198/004017003000000014
  3. Capizzi, G. and G. Masarotto, "An enhanced control chart for start-up processes and short runs," Quality Technology and Quantitative Management, Vol. 9, No.2(2012), pp.189-202. https://doi.org/10.1080/16843703.2012.11673285
  4. Crowder, S.V., "An SPC model for short production runs:minimizing expected cost," Technometrics, Vol. 34, No.1(1992), pp.64-73. https://doi.org/10.2307/1269553
  5. Del Castillo, E. and D.C. Montgomery, "Shortrun statistical process control:Q-Chart enhancements and alternative methods," Quality and Reliability Engineering International, Vol.10, No.2(1994), pp.87-97. https://doi.org/10.1002/qre.4680100203
  6. Gary, S.M. and J.S. Costas, Fundamentals of Semiconductor Manufacturing and Process Control, Wiley, New Jersey, 2006.
  7. Hawkins, D.M., "Self-starting CUSUM charts for location and scale," The Statistician, Vol. 36, No.4(1987), pp.299-316. https://doi.org/10.2307/2348827
  8. Hwang, J.Y. and H.C. Lee, "Parametric yield modeling using hidden variable logistic regression," Journal of Quality Technology, Vol.6, No.4(2014), pp.323-339.
  9. Kutner, M.H., C.J. Nachtsheim, J. Neter, and W. Li, Applied Linear Statistical Models, New York, McGraw-Hill, 2005.
  10. Nurani, R.K. and J.G. Shanthikumar, "Process control for items produced in lots with inter and intra lot variations," International Journal of Industrial Engineering, Vol.7, No.1 (2000), pp.57-66.
  11. Quesenberry, C.P., "SPC Q charts for start-up processes and short or long runs," Journal of Quality Technology, Vol.23, No.3(1991), pp.213-224.
  12. Quesenberry, C.P., "SPC Q charts for a binomial parameter p:short or long Runs," Journal of Quality Technology, Vol.23, No.3(1991), pp.239-246. https://doi.org/10.1080/00224065.1991.11979329
  13. Quesenberry, C.P., "SPC Q charts for a Poisson parameter $\lambda$:short or long runs," Journal of Quality Technology, Vol.23, No.3(1991), pp.213-224. https://doi.org/10.1080/00224065.1991.11979327
  14. Quesenberry, C.P., "On properties of Q charts for variables," Journal of Quality Technology, Vol.27, No.3(1995), pp.184-203. https://doi.org/10.1080/00224065.1995.11979592
  15. Quesenberry, C.P., "On properties of binomial Q charts for attributes," Journal of Quality Technology, Vol.27, No.3(1995), pp. 204-213. https://doi.org/10.1080/00224065.1995.11979593
  16. Quesenberry, C.P., "Geometric Q charts for high quality processes," Journal of Quality Technology, Vol.27, No.3(1995), pp.304-315. https://doi.org/10.1080/00224065.1995.11979610
  17. Woodall, W.H. and D.C. Montgomery, "Some current directions in the theory and application of statistical process monitoring," Journal of Quality Technology, Vol.46, No.1(2014), pp.78-94. https://doi.org/10.1080/00224065.2014.11917955
  18. Woodall, W.M. and E.V. Thomas, "Statistical process control with several components of common cause variability," IIE Transactions, Vol.27, No.6(1995), pp.757-764. https://doi.org/10.1080/07408179508936792
  19. Zantek, P.F., "Run-length distributions of Q-chart schemes," IIE Transactions, Vol.37, No.11(2005), pp.1037-1045. https://doi.org/10.1080/07408170500232297
  20. Zantek, P.F., "Design of cumulative sum schemes for start-up processes and short runs," Journal of Quality Technology, Vol.38, No.4(2006), pp.365-375. https://doi.org/10.1080/00224065.2006.11918624
  21. Zantek P.F. and S.T. Nestler, "Performances and properties of Q-statistic monitoring schemes," Naval Research Logistics, Vol.56, No.3 (2009), pp.279-292. https://doi.org/10.1002/nav.20330