Skip to main content
SpringerLink
Log in

An improved SPRT control chart for monitoring process mean

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

The sequential probability ratio test (SPRT) chart is a desirable tool for monitoring manufacturing processes due to its high effectiveness. It is especially suitable for applications where testing is very expensive or destructive, such as the automobile airbags test and unaxial tensile test. This article proposes a design algorithm for the SPRT chart in which the reference value (γ) of the SPRT chart is optimized. The design algorithm increases the overall effectiveness of the SPRT chart by more than 10% on average. Moreover, the improvement in detection effectiveness is achieved without any additional difficulty in implementation. A design table is also provided to facilitate quality engineers to design the SPRT chart.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Wu Z, Xie M, Liu QC, Zhang Y (2006) SXC control chart. Int J Adv Manuf Technol 30:444–451

    Article  Google Scholar 

  2. Sheu SH, Tau SH (2006) Generally weighted moving average control chart for monitoring process variability. Int J Adv Manuf Technol 30:452–458

    Article  Google Scholar 

  3. Jiao JX, Helo PT (2008) Optimization design of a CUSUM control chart based on Taguchi’s loss function. Int J Adv Manuf Technol 35:1234–1243

    Article  Google Scholar 

  4. Arnold JC, Reynolds MR Jr (2001) CUSUM control charts with variable sample sizes and sampling intervals. J Qual Technol 33:66–81

    Google Scholar 

  5. Zhang S, Wu Z (2007) A CUSUM scheme with variable sample sizes for monitoring process shifts. Int J Adv Manuf Technol 33:977–987

    Article  Google Scholar 

  6. Stoumbos ZG, Reynolds MR Jr (1997) Control charts applying a sequential test at fixed sampling intervals. J Qual Technol 29:21–40

    Google Scholar 

  7. Wald A (1947) Sequential analysis. Wiley, New York

    MATH  Google Scholar 

  8. Lynn J (1996) Calculating the exact characteristics of truncated sequential probability ratio tests using mathematica. Proceedings of 12th Symposium on Comput Stat 26–30

  9. Lee GP, Stefan SH, George WO (1996) Improved SPRT and CUSUM procedures with compressed-limit Gauges. IIE Trans 28:489–496

    Article  Google Scholar 

  10. Stoumbos ZG, Reynolds MR Jr (1997) Corrected diffusion theory approximations in evaluating properties of SPRT charts for monitoring a process mean. Nonlinear An 30:3987–3996

    Article  MATH  MathSciNet  Google Scholar 

  11. Reynolds MR Jr, Stoumbos ZG (1998) The SPRT chart for monitoring a proportion. IIE Trans 30:545–561

    Google Scholar 

  12. Stoumbos ZG, Reynolds MR Jr (2001) The SPRT control chart for the process mean with samples starting at fixed times. Nonlinear An 2:1–34

    Article  MATH  Google Scholar 

  13. Li Y, Pu XL, Tsung FG (2009) Adaptive charting schemes based on double sequential probability ratio tests. Qual Reliab Eng Int 25:21–39

    Article  Google Scholar 

  14. Corsini G, Dalle Mese E, Marchetti G, Verrazzani L (1985) Design of the SPRT for radar target detection. IEE Proceedings F 132:139–148

    Google Scholar 

  15. Bagchi TP (1992) Sequential tests to monitor lot attribute quality in the presence of inspection errors. Opsearch 29:165–183

    MATH  Google Scholar 

  16. Stefan A, Ali B, Ingvar C (1996) Quality monitoring in robotized welding using sequential probability ratio test. IEEE Region 10 Annual Int Conference 2:635–640

    Google Scholar 

  17. Yu FJ, Low CY, Cheng SS (2003) Design for an SPRT control scheme based on linguistic data. Int J of Prod Res 41:1299–1309

    Article  MATH  Google Scholar 

  18. Kwon D, Azarian MH, Pecht MG (2008) Early detection of interconnect degradation using RF impedance and SPRT. Int Conf Prognostics and Health Management 1–8

  19. Stoumbos ZG, Reynolds MR Jr (1996) Control charts applying a general sequential test at each sampling point. Sequential An 15:159–183

    Article  MATH  MathSciNet  Google Scholar 

  20. Stoumbos ZG, Reynolds MR Jr (1996b) Variable sampling rate control charts with sampling at fixed intervals. Proceedings of the Fifth Industrial Eng Res Conference 687–692

  21. Ou YJ, Wu Z, Lee KM, Chen SL (2009) A highly effective control SPRT chart for monitoring process mean. Technical Report, School of Mechanical and Aerospace Engineering, Nanyang Technological University

  22. Wu Z, Jiao JX, Yang M, Liu Y, Wang ZJ (2009) An enhanced adaptive CUSUM control chart. IIE Trans 41:642–653

    Article  Google Scholar 

  23. Sparks RS (2000) Cusum charts for signalling varying location shifts. J Qual Technol 32:157–171

    Google Scholar 

  24. Reynolds MR Jr, Stoumbos ZG (2004) Should observations be grouped for effective process monitoring. J Quality Technol 36:343–366

    Google Scholar 

  25. Shu LJ, Jiang W (2006) A Markov chain model for the adaptive CUSUM control chart. J Qual Technol 38:135–147

    Google Scholar 

  26. Wu Z, Yang M, Jiang W, Khoo MBC (2008) Optimization designs of the combined shewhart-CUSUM control charts. Comput Stat Data An 53:496–506

    Article  MATH  Google Scholar 

  27. Reynolds MR Jr, Stoumbos ZG (2004) Control charts and the efficient allocation of sampling resources. Technometrics 46:200–214

    Article  MathSciNet  Google Scholar 

  28. Reynolds MR Jr, Stoumbos ZG (2006) Comparisons of some exponentially weighted moving average control charts for monitoring the process mean and variance. Technometrics 48:550–567

    Article  MathSciNet  Google Scholar 

  29. Domangue R, Patch SC (1991) Some omnibus exponentially weighted moving average statistical process monitoring schemes. Technometrics 33:299–313

    Article  MATH  Google Scholar 

  30. Wu Z, Tian Y (2005) Weighted-loss-function CUSUM chart for monitoring mean and variance of a prod process. Int J Prod Res 43:3027–3044

    Article  MATH  Google Scholar 

  31. Yu KT, Sheu SH, Chen KS (2007) The evaluation of process capability for a machining center. Int J Adv Manuf Technol 33:505–510

    Article  Google Scholar 

  32. Reynolds MR Jr, Amin RW, Arnold JC (1990) CUSUM charts with variable sampling intervals. Technometrics 32:371–384

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, Singapore, 639798

    Yanjing Ou, Zhang Wu, Songlin Chen & Ka Man Lee

Authors
  1. Yanjing Ou
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zhang Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Songlin Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ka Man Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Zhang Wu.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ou, Y., Wu, Z., Chen, S. et al. An improved SPRT control chart for monitoring process mean. Int J Adv Manuf Technol 51, 1045–1054 (2010). https://doi.org/10.1007/s00170-010-2675-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-010-2675-6

Keywords

Search

Navigation