Skip to main content
SpringerLink
Log in

Special Control Charts Using Intelligent Techniques: EWMA Control Charts

  • Chapter
  • First Online:
Intelligent Decision Making in Quality Management

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 97))

Abstract

In this chapter we consider the economical design of EWMA zone control charts for set of machines operating under JPS (Jidoka Production System ). We provide an extensive literature review of intelligent systems in quality control deductively to fit our purposes. It starts with an overview of quality control charts; then, reviews charts designed for special purposes such as EWMA, CUSUM and zone control charts . Finally, as particularly related to this study, reviews of economical design and intelligent applications of EWMA are provided. We discuss and review Jidoka Production System and motivation of operating such a system. We suggest an intelligent control and repair system such that in a production system, machines are individually controlled and repaired when an out-of-control signal is triggered in the zone with the tight control limits, however a system-wide shut down and repair is conducted when the out-of-control signal is from beyond the inner (tight) control limits which is considered as an opportunity for repair and calibration of all machines. We illustrate and investigate the behaviour of control parameters, namely sample size , sampling interval and control limits, via a numerical study of a three-machine system through simulation. We also provide insights for implementation of several metaheuristics for the system setting discussed in this chapter.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Abbas, N., Riaz, M., Does, R.J.M.M.: Mixed exponentially weighted moving average–cumulative sum charts for process monitoring. Qual. Reliab. Eng. Int. 29(3), 345–356 (2012)

    Article  Google Scholar 

  • Aparisi, F., Garcı́a-Dı́az, J.C.: Optimization of univariate and multivariate exponentially weighted moving-average control charts using genetic algorithms. Comput. Oper. Res. 31(9), 1437–1454 (2004)

    Google Scholar 

  • Aparisi, F., García-Díaz, J.C.: Design and optimization of EWMA control charts for in-control, indifference, and out-of-control regions. Comput. Oper. Res. 34(7), 2096–2108 (2007)

    Article  MATH  Google Scholar 

  • Benneyan, J.C., Lloyd R.C., Plsek, P.E.: Statistical process control as a tool for research and healthcare improvement. Qual. Saf. Health Care 12, 458–464 (2003)

    Google Scholar 

  • Berk, E., Toy, A.O.: Quality control chart design under jidoka. Naval Res. Logist. 56, 465–477 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  • Butler, S.W., Stefani, J.A.: Supervisory run-to-run control of polysilicon gate etch using in situ ellipsometry. IEEE Trans. Semicond. Manuf. 7(2), 193–201 (1994)

    Article  Google Scholar 

  • Celano, G., Fichera, S.: Multiobjective economic design of an X control chart. Comput. Ind. Eng. 37, 129–132 (1999)

    Article  Google Scholar 

  • Charongrattanasakul, P., Pongpullponsak, A.: Minimizing the cost of integrated systems approach to process control and maintenance model by EWMA control chart using genetic algorithm. Expert Syst. Appl. 38(5), 5178–5186 (2011)

    Article  Google Scholar 

  • Chou, C.-Y., Chen, C.-H.: Economic design of variable sampling intervals T2 control charts using genetic algorithms. Expert Syst. Appl. 30, 233–242 (2006)

    Article  Google Scholar 

  • Chou, C.Y., Cheng, J.C., Lai, W.T.: Economic design of variable sampling intervals EWMA charts with sampling at fixed times using genetic algorithms. Expert Syst. Appl. 34, 419–426 (2008)

    Article  Google Scholar 

  • Costa, A.F.B.: Joint economic design of \( \bar{X} \) and R control charts for process subject to two independent assignable causes. IIE Trans. 25, 27–33 (1993)

    Google Scholar 

  • Costa, A.F.B.: Joint X chart with variable parameters. J. Qual. Technol. 31, 408–416 (1999)

    Google Scholar 

  • Crowder, S.V.: Design of exponentially weighted moving average scheme. J. Qual. Technol. 21, 155–162 (1989)

    Google Scholar 

  • Davis, R.B., Krehbiel, T.C.: Shewhart and zone control chart performance under linear trend. Commun. Stat. —Simul. Comput. 31(1), 91–96 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  • Davis, R.B., Jin, C., Guo, Y.: Improving the performance of the zone control chart. Commun. Stat.—Theory Methods 23, 3557–3565 (1994)

    Google Scholar 

  • Davis, R.B., Homer, A., Woodall, W.H. Performance of the zone control chart. Commun. Stat.—Theory Methods 19, 1581–1587 (1990)

    Google Scholar 

  • De Vries, A., Reneau, J.K.: Application of statistical process control charts to monitor changes in animal production systems. J. Anim. Sci. 88, E11–E24 (2010)

    Article  Google Scholar 

  • Diaz, M., Neuhauser, D.: Pasteur and parachutes: when statistical process control is better than a randomized controlled trial. Qual. Saf. Health Care 14, 140–143 (2005)

    Article  Google Scholar 

  • Duncan, A.J.: The economic design of \( {\bar{\text{X}}} \) charts used to maintain current control of process. J. Am. Stat. Assoc. 51, 228–242 (1956)

    Google Scholar 

  • Fan, S.-K.S., Wang, C.-Y.: On-line tuning system of multivariate dEWMA control based on a neural network approach. Int. J. Prod. Res. 46(13), 3459–3484 (2008)

    Article  MATH  Google Scholar 

  • Flaig, J.J.: Zone control charts. http://www.e-AT-USA.com (2004)

  • Gan, F.F.: Computing the percentage points of the run length distribution of an exponentially weighted moving average control chart. J. Qual. Technol. 23, 359–362 (1991)

    Google Scholar 

  • Haq, A., Brown, J., Moltchanova, E.: New synthetic EWMA and synthetic CUSUM control charts for monitoring the process mean. Qual. Reliab. Eng. Int. (2014). doi:10.1002/qre.1747

    Google Scholar 

  • Hawkins, D.M., Olwell, D.H.: Cumulative Sum Charts and Charting for Quality Improvement. Springer, New York (1998)

    Book  MATH  Google Scholar 

  • Hawkins, D.M., Wu, Q.: The CUSUM and the EWMA head-to-head. Qual. Eng. 26, 215–222 (2014)

    Article  Google Scholar 

  • He, H., Grigoryan, A., Sigh, M.: Design of double- and triple-sampling X-bar control charts using genetic algorithms. Int. J. Prod. Res. 40(6), 1387–1404 (2002)

    Article  MATH  Google Scholar 

  • Ho, C., Case, K.E.: An economic design of the zone control chart for jointly monitoring process centering and variation. Comput. Ind. Eng. 26(2), 213–221 (1994a)

    Article  Google Scholar 

  • Ho, C., Case, K.E.: Economic design of control charts: a literature review for 1981–1991. J. Qual. Technol. 26, 39–53 (1994b)

    Google Scholar 

  • Hopgood, A.A. Intelligent Systems for Engineers and Scientists, CRC Press, Boca Raton (2012)

    Google Scholar 

  • Hoss, M., ten Caten, C.S.: Lean schools of thought. Int. J. Prod. Res. 51(11), 3270–3282 (2013)

    Article  Google Scholar 

  • Jaehn, A.H.: Zone control charts—SPC made easy. Quality 26, 51–53 (1987)

    Google Scholar 

  • Jaehn, A.H.: Zone control charts find new applications. ASQC Qual. Congr. Trans. 890–895 (1989)

    Google Scholar 

  • Kim, J., Gershwin, S.B.: Integrated quality and quantity modeling of a production line. OR Spectrum 27, 287–314 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  • Lee, P.-H., Torng, C.-C., Liao, L.-F.: An economic design of combined double sampling and variable sampling interval X control chart. Int. J. Prod. Econ. 138, 102–106 (2012)

    Article  Google Scholar 

  • Lin, S.-N., Chou, C.-Y., Wang, S.-L., Liu, H.-R.: Economic design of autoregressive moving average control chart using genetic algorithms. Expert Syst. Appl. 39, 1793–1798 (2012)

    Article  Google Scholar 

  • Lorenzen, T.J., Vance, L.C.: The economic design of control charts: a unified approach. Technometrics 28, 3–10 (1986)

    Article  MathSciNet  MATH  Google Scholar 

  • Lucas, J.M., Saccucci, M.S.: Exponentially weighted moving average control schemes: properties and enhancements (with discussion). Technometrics 32, 1–29 (1990)

    Article  MathSciNet  Google Scholar 

  • Monden, Y.: Toyota Production System: Practical Approach to production Management. Management Institute Engineering and Management Press, Norcross (1983)

    Google Scholar 

  • Montgomery D.C.: The economic design of control charts: a review and literature survey. J. Qual. Technol. 1, 24–32 (1980a)

    Google Scholar 

  • Montgomery, D.C.: The economic design of control charts: a review and literature survey. J. Qual. Technol. 12, 75–81 (1980b)

    Google Scholar 

  • Montgomery, D.C.: Introduction to Statistical Quality Control. Wiley, New York (1996)

    MATH  Google Scholar 

  • Montgomery, D.C.: Introduction to Statistical Quality Control, 2nd edn. Wiley, New York (1991)

    Google Scholar 

  • Montgomery, D.C., Torng, J.C.-C., Cocgran, J.K., Lawrence, F.P.: Statistically constrained economic design of the EWMA control chart. J. Qual. Technol. 27(3), 250–256 (1995)

    Google Scholar 

  • Montgomery D.C.: Introduction to Statistical Quality Control, 6th edn. Wiley, New York (2009)

    Google Scholar 

  • Montgomery, D.C.: Introduction to Statistical Quality Control, 7th edn. Wiley, New York (2013)

    MATH  Google Scholar 

  • Nenes, G.: A new approach for the economic design of fully adaptive control charts. Int. J. Prod. Econ. 131(2), 631–642 (2011)

    Article  Google Scholar 

  • Neubauer, A.S.: The EWMA control chart: properties and comparison with other quality-control procedures by computer simulation. Clin. Chem. 43(4), 594–601 (1997)

    Google Scholar 

  • Negnevitsky, M. Artificial Intelligence: a Guide to Intelligent Systems, Addison-Wesley, Boston (2011)

    Google Scholar 

  • Niaki, S.T.A., Ershadi, M.J., Malaki, M.: Economic and economic-statistical designs of MEWMA control charts, a hybrid taguchi loss, markov chain and genetic algorithm approach. Int. J. Adv. Manuf. Technol. 48, 283–296 (2010)

    Article  Google Scholar 

  • Niaki, S.T.A., Gazaneh, F.M. Toosheghanian, M. Economic design of variable sampling interval \( {\bar{\text{X}}} \) control charts for monitoring correlated non normal samples. Commun. Stat.—Theory Methods 42(18), 3339–3358 (2013)

    Google Scholar 

  • Niaki, S.T.A., Malaki, M., Ershadi, M.J.: A particle swarm optimization approach on economic and economic-statistical designs of MEWMA control charts. ScientiaIranica E 18(6), 1529–1536 (2011)

    Google Scholar 

  • Niaki, S.T.A., Ershadi, M.J.: A hybrid ant colony Markov chain, and experimental design approach for statistically constrained economic design of MEWMA control charts. Expert Syst. with Appl. 39(3), 3265–3275 (2012)

    Article  Google Scholar 

  • Ohno, T.: Toyota Production System, Productivity Press, Boca Raton (1988)

    Google Scholar 

  • Page, E.S.: Continuous inspection schemes. Biometrika 41, 100–115 (1954)

    Article  MathSciNet  MATH  Google Scholar 

  • Park, C.: Economic design of charts when signals may be misclassified and the bounded reset chart. IIE Trans. 45(4), 436–448 (2013)

    Article  Google Scholar 

  • Park, C., Lee, J., Kim, Y.: Economic design of a variable sampling rate EWMA chart. IIE Trans. 36, 387–399 (2004)

    Google Scholar 

  • Parkash, V., Kumar, D., Rajoria, R.: Statistical Process Control. IJRET: Int. J. Res. Eng. Technol. 2(8), 70–72 (2013)

    Google Scholar 

  • Pignatiello, J.J., Tsai, A.: Optimal economic design of control chart when cost model parameters are not known. IIE Trans. 20, 103–110 (1988)

    Article  Google Scholar 

  • Quesenberry, C.P.: SPC Methods for Quality Improvement. Wiley, New York (1997)

    Google Scholar 

  • Reynolds Jr, M.R., Amin, R.W., Arnold, J.C., Nachlas, J.A.: X charts with variable sampling intervals. Technometrics 30, 181–192 (1988)

    MathSciNet  Google Scholar 

  • Roberts, S.W.: Control chart tests based on geometric moving averages. Technometrics 1, 239–250 (1959)

    Article  Google Scholar 

  • Robinson, P.B., Ho, T.Y.: Average run lengths of geometric moving average charts by numerical methods. Technometric 20, 85–93 (1978)

    Article  MATH  Google Scholar 

  • Saghaei, A., Ghomi, S.M.T.F., Jaberi, S.: Economic design of exponentially weighted moving average control chart based on measurement error using genetic algorithm. Reliab. Eng. Int. Qual. doi:10.1002/qre.1538

    Google Scholar 

  • Schonberger, R.J.: Japanese production management: an evolution—with mixed success. J. Oper. Manag. 25(2), 403–419 (2007)

    Article  Google Scholar 

  • Serel, A.S.: Economic design of EWMA control charts based on loss function. Math. Comput. Model. 49, 745–759 (2009)

    Article  MATH  Google Scholar 

  • Serel, D.A., Moskowitz, H.: Joint economic design of EWMA control charts for mean and variance. Eur. J. Oper. Res. 184, 157–168 (2008)

    Google Scholar 

  • Schalkoff, R.J.: Intelligent Systems: Principles. Jones & Bartlett Publishers, Paradigms and Pragmatics (2009)

    Google Scholar 

  • Shewhart, W.A.: Some Applications of Statistical Methods. ASQ Publications (1924)

    Google Scholar 

  • Shingo, S.: A Study of the Toyota Production System from an Industrial Engineering Viewpoint. Productivity Press, Portland (1989)

    Google Scholar 

  • Smith, Taber H., Boning, Duane S.: Artificial neural network exponentially weighted moving average controller for semiconductor processes. J. Vac. Sci. Technol. A 15, 1377–1384 (1997a)

    Article  Google Scholar 

  • Smith, T.H., Boning, D.S.: A self-tuning EWMA controller utilizing artificial neural network function approximation techniques. Compon. Packag. Manuf. Technol. Part C, IEEE Trans. 20(2), 121–132 (1997b)

    Article  Google Scholar 

  • Solodky, C., Chen, H., Jones, P.K., Katcher, W., Neuhauser, D.: Patients as partners in clinical research: a proposal for applying quality improvement methods to patient care. Med. Care 36(Suppl.):AS13 AS20 (1998)

    Google Scholar 

  • Spanos, C.J.: Statistical process control in semiconductor manufacturing. Proc. IEEE 819–830 (1992)

    Google Scholar 

  • Su, C.-T., Hsu, C.-C.: On-line tuning of a single EWMA controller based on the neural technique. Int. J. Prod. Res. 42(11), 2163–2178 (2004a)

    Article  Google Scholar 

  • Su, C.-T., Hsu, C.-C.: A time-varying weights tuning method of the double EWMA controller. Omega 32(6), 473–480 (2004b)

    Article  Google Scholar 

  • Thor, J., Lundberg, J., Ask, J., Olsson, J., Carli, C., PukkHarenstam, K., Brommels, M.: Application of statistical process control in healthcare and improvement: a systematic review. Qual. Saf. Health Care 16(387), 399 (2007)

    Google Scholar 

  • Tolley, G.O., English, J.R.: Economic designs of constrained EWMA and combined EWMA-X-bar control schemes. IIE Trans. 33, 429–436 (2001)

    Google Scholar 

  • Torng, C.-C., Lee, P.-H., Liao, N.-Y.: An economic-statistical design of double sampling \( {\bar{\text{X}}} \) control chart. Int. J. Prod. Econ. 120(2), 495–500 (2009a)

    Google Scholar 

  • Torng, C.-C., Lee, P.-H., Liao, H.-S., Liao, N.-Y.: An economic design of double sampling \( {\bar{\text{X}}} \) charts for correlated data using genetic algorithms. Expert Syst. Appl. 36(10), 12621–12626 (2009b)

    Google Scholar 

  • Toyota Motor Corporation (1996). The Toyota production system

    Google Scholar 

  • Vance, L.C.: A bibliography of statistical quality control chart techniques, 1970–1980. J. Qual. Technol. 15, 59–62 (1983)

    Google Scholar 

  • Vargas, V.C.C., Lopes, L.F.D., Souza, A.M.: Comparative study of the performance of the CuSum and EWMA control charts. Comput. Ind. Eng. 46(4), 707–724 (2004)

    Article  Google Scholar 

  • Vommi, V.B., Seetala, S.N.: A simple approach for robust economic design of control charts. Comput. Oper. Res. 34(7), 2001–2009 (2007)

    Article  MATH  Google Scholar 

  • Waldman, K.H.: Bounds for the distribution of the run length of geometric moving average charts. J. Roy. Statist. Soc. Ser. B (Appl. Statist.), 35, 151–158 (1986)

    Google Scholar 

  • Electric, Western: Statistical Quality Control Handbook. AT& T, Indianapolis (1956)

    Google Scholar 

  • Woodall, W.H.: Weakness of the economic design of control charts. Technometrics 28, 408–409 (1986)

    Article  Google Scholar 

  • Woodall, W.H.: Conflicts between Deming’s philosophy and the economic design of control charts. In: Lenz, H.J., Wetherill, G.B., Wilrich, P.T. (eds.) Frontiers in Statistical Quality Control 3, pp. 155–168. Physica-Verlag, Heidelberg (1987)

    Google Scholar 

  • Woodall, W.H.: The use of control charts in health-care and public-health surveillance. J. Qual. Technol. 38, 89–104 (2006)

    Google Scholar 

  • Woodall, W.H., Lorenzen, T.J., Vance, L.C.: Weaknesses of the economic design of control charts. Technometrics 28, 408–410 (1986)

    Article  Google Scholar 

  • Zaman, B., Riaz, M., abbas, N., Does, R.J.M.M.: Mixed cumulative sum–exponentially weighted moving average control charts: an efficient way of monitoring process location. Qual. Reliab. Eng. Int. doi:10.1002/qre.1678

    Google Scholar 

  • Zhou, W.-H., Zhu, G.-L.: Economic design of integrated model of control chart and maintenance. Math. Comput. Model. 47, 1389–1395 (2008)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Industrial Engineering, Istanbul Bilgi University, 34060, Eyüp/Istanbul, Turkey

    Bulut Aslan, Yeliz Ekinci & Ayhan Özgür Toy

Authors
  1. Bulut Aslan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yeliz Ekinci
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ayhan Özgür Toy
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Bulut Aslan .

Editor information

Editors and Affiliations

  1. İşletme Fakültesi, Istanbul Technical University, Istanbul, Turkey

    Cengiz Kahraman

  2. Industrial Engg Dept, Istanbul Technical University, Istanbul, Turkey

    Seda Yanik

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Aslan, B., Ekinci, Y., Toy, A.Ö. (2016). Special Control Charts Using Intelligent Techniques: EWMA Control Charts. In: Kahraman, C., Yanik, S. (eds) Intelligent Decision Making in Quality Management. Intelligent Systems Reference Library, vol 97. Springer, Cham. https://doi.org/10.1007/978-3-319-24499-0_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-24499-0_4

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24497-6

  • Online ISBN: 978-3-319-24499-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation