Skip to main content
Log in

A synthetic control chart for monitoring process dispersion with sample range

  • Original Article
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

A synthetic control chart for monitoring the changes in the standard deviation of a normally distributed process is proposed in this paper. The synthetic chart consists of the sample range (R) chart and the conforming run-length (CRL) chart. The R chart can be viewed as a special case of the synthetic chart. The operation, design and performance of this chart are described. Average run- length comparisons between other procedures and the synthetic chart are presented. It indicates that the synthetic chart is a good alternative for monitoring process dispersion. The variable sampling interval (VSI) schemes, as an enhancement to the synthetic chart, are discussed to further improve the chart performance. An example is presented to illustrate the application of synthetic chart and its VSI scheme.

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

Access this article

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

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Nelson LS (1990) Monitoring reduction in variation with a range chart. J Qual Technol 22:163–165

    Article  Google Scholar 

  2. Lowry CA, Champ CW, Woodall WH (1995) The performance of control charts for monitoring process variation. Commun Stat Simul Comput 24:409–437

    Article  MathSciNet  Google Scholar 

  3. Page ES (1963) Controlling the standard deviation by CUSUM and warning lines. Technometrics 5:307–315

    Article  Google Scholar 

  4. Alt FB (1984) Multivariate quality control. In: Kotz S, Johnson NL, Read CR (eds) The encyclopedia of statistical sciences. Wiley, New York, pp 110–122

  5. Tuprah K, Ncube M (1987) A comparison of dispersion quality control charts. Sequential Anal 6:155–163

    Article  Google Scholar 

  6. Crowder SV, Hamilton MD (1992) An EWMA for monitoring a process standard deviation. J Qual Technol 24:12–21

    Article  Google Scholar 

  7. Chang TC, Gan FF (1994) Optimal designs of one-sided EWMA charts for monitoring a process variance. J Stat Comput Simul 49:33–48

    Article  Google Scholar 

  8. Chang TC, Gan FF (1995) A cumulative sum control chart for monitoring process variance. J Qual Technol 27:109–119

    Article  Google Scholar 

  9. Acosta-Mejia CA (1998) Monitoring reduction in variability with the range. IIE Trans 30:515–523

    Google Scholar 

  10. Srivastava MS (1997) CUSUM procedure for monitoring variability. Commun Stat Theory Methods 26:2905–2926

    Article  Google Scholar 

  11. Acosta-Mejia CA, Pignatiello JJ Jr., Rao BV (1999) A comparison of control charting procedures for monitoring process dispersion. IIE Trans 31:569–579

    Google Scholar 

  12. Klein M (2000) Modified S-charts for controlling process variability. Commun Stat Simul Comput 29:919–940

    Article  Google Scholar 

  13. Wu A, Spedding TA (2000) A synthetic control chart for detecting small shifts in the process mean. J Qual Technol 32:32–38

    Article  Google Scholar 

  14. Calzada ME, Scariano SM (2001) The robustness of the synthetic control chart to non-normality. Commun Stat Simul Comput 30:311–326

    Article  Google Scholar 

  15. Davis RB, Woodall WH (2002) Evaluating and improving the synthetic control chart. J Qual Technol 34:200–208

    Article  Google Scholar 

  16. Pearson ES, Hartley HO (1942) The probability integral of the range in samples of n observations from a normal population. Biometrika 32:301–310

    Article  MathSciNet  Google Scholar 

  17. Bourke PD (1991) Detecting a shift in fraction nonconforming using run-length control charts with 100% inspection. J Qual Technol 23:225–238

    Article  Google Scholar 

  18. Kaminsky FC, Benneyan JC, Davis RD (1992) Statistical control charts based on a geometric distribution. J Qual Technol 24:63–69

    Google Scholar 

  19. Xie M, Goh TN, Lu XS (1998) A comparative study of CCC and CUSUM charts. Qual Reliabil Eng Int 14:339–345

    Article  Google Scholar 

  20. Wu Z, Yeo SH, Fan H( 2000) A comparative study of the CRL-type control charts. Qual Reliabil Eng Int 16:269–279

    Article  Google Scholar 

  21. Yang Z, Xie M, Kuralmani V, Tsui KL (2002) On the performance of geometric charts with estimated control limits. J Qual Technol 34:448–458

    Article  Google Scholar 

  22. Reynolds MR Jr., Amin RW, Arnold JC, Nachlas JA (1988) X̄ charts with variable sampling intervals. Technometrics 30:181–192

    MathSciNet  Google Scholar 

  23. Runger GC, Pignatiello JJ Jr. (1991) Adaptive sampling for process control. J Qual Technol 23:135–155

    Article  Google Scholar 

  24. Aparisi F, Haro CL (2001) Hotelling’s T2 control chart with variable sampling intervals. Int J Prod Res 39:3127–3140

    Article  Google Scholar 

  25. Tagaras G (1998) A survey of recent developments in the design of adaptive control charts. J Qual Technol 30:212–231

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to F.-L. Chen.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chen, FL., Huang, HJ. A synthetic control chart for monitoring process dispersion with sample range. Int J Adv Manuf Technol 26, 842–851 (2005). https://doi.org/10.1007/s00170-003-2010-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-003-2010-6

Keywords

Navigation