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Monitoring the ratio of population means of a bivariate normal distribution using CUSUM type control charts

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Abstract

Continuous surveillance of the ratio of population means of bivariate normal distributions is a quality control issue worth of consideration in several manufacturing and service-oriented companies. For this reason, some recent studies have investigated traditional and advanced Shewhart control charts to perform on-line monitoring of this kind of ratio. Anyway, Shewhart control charts are known to be insensitive to small and moderate shift sizes. Up to now, CUSUM control charts have not yet been considered for this quality control problem. In this paper, we propose and investigate the statistical properties of two Phase II one-sided CUSUM control charts for monitoring the ratio of population means of a bivariate normal distribution. Several figures and tables are provided to show the sensitivity of the two CUSUM charts to different deterministic shift sizes and their performance for the random shift size condition. In most cases, the numerical results demonstrate that the proposed CUSUM control charts are very sensitive to shifts in the ratio. An illustrative example comments the use of these charts in a simulated quality control problem from the food industry.

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References

  • Adamski K, Human S, Bekker A (2012) A generalized multivariate beta distribution: control charting when the measurements. Stat Pap 53(4):1045–1064

    Article  MATH  Google Scholar 

  • Brook D, Evans D (1972) An approach to the probability distribution of CUSUM run length. Biometrika 59(3):539–549

    Article  MathSciNet  MATH  Google Scholar 

  • Castagliola P, Maravelakis PE (2011) A CUSUM control chart for monitoring the variance when parameters are estimated. J Stat Plan Inference 141(4):1463–1478

    Article  MathSciNet  MATH  Google Scholar 

  • Castagliola P, Celano G, Fichera S (2009) A new CUSUM-\({S}^2\) control chart for monitoring the process variance. J Qual Maint Eng 15(4):344–357

    Article  Google Scholar 

  • Cedilnik A, Kosmelj K, Blejec A (2004) The distribution of the ratio of jointly normal variables. Metodoloski Zvezki 1(1):99–108

    Google Scholar 

  • Celano G, Castagliola P (2016a) Design of a phase II control chart for monitoring the ratio of two normal variables. Qual Reliab Eng Int 32(1):291–308

  • Celano G, Castagliola P (2016b) A synthetic control chart for monitoring the ratio of two normal variables. Qual Reliab Eng Int 32(2):681–696

  • Celano G, Castagliola P, Nenes G, Fichera S (2013) Performance of \(t\) control charts in short runs with unknown shift sizes. Comput Ind Eng 64:56–68

    Article  Google Scholar 

  • Celano G, Castagliola P, Faraz A, Fichera S (2014) Statistical performance of a control chart for individual observations monitoring the ratio of two normal variables. Qual Reliab Eng Int 30(8):1361–1377

    Article  Google Scholar 

  • Champ CW, Rigdon SE (1991) A a comparison of the markov chain and the integral equation approaches for evaluating the run length distribution of quality control charts. Commun Stat: Simul Comput 20(1):191–204

    Article  MATH  Google Scholar 

  • Chen A, Chen Y (2007) Design of EWMA and CUSUM control charts subject to random shift sizes and quality impacts. IIE Trans 39(12):1127–1141

    Article  Google Scholar 

  • Chen N, Li Z, Ou Y (2015) Multivariate exponentially weighted moving average chart for monitoring Poisson observations. J Qual Technol 47(3):252

    Article  Google Scholar 

  • Davis R, Woodall W (1991) Evaluation of control charts for ratios. In: 22nd annual Pittsburgh conference on modeling and simulation, Pittsburgh

  • Faraz A, Celano G, Saniga E, Heuchenne C, Fichera S (2014) The variable parameters \({T^{2}}\) chart with run rules. Stat Pap 55(4):933–950

    Article  MathSciNet  MATH  Google Scholar 

  • Geary R (1930) The frequency distribution of the quotient of two normal variates. J R Stat Soc 93(3):442–446

    Article  MATH  Google Scholar 

  • Graham M, Chakraborti S, Mukherjee A (2014) Design and implementation of CUSUM exceedance control charts for unknown location. Int J Prod Res 52(18):5546–5564

    Article  Google Scholar 

  • Hawkins D, Wu Q (2014) The CUSUM and theEWMA head-to-head. Qual Eng 26(2):215–222

    Article  Google Scholar 

  • Hawkins DM, Olwell D (1998) Cumulative sum charts and charting for quality improvement. Springer, New York

    Book  MATH  Google Scholar 

  • Hayya J, Armstrong D, Gressis N (1975) A note on the ratio of two normally distributed variables. Manag Sci 21(11):1338–1341

    Article  MATH  Google Scholar 

  • Knoth S (2005) Fast initial response features for EWMA control charts. Stat Pap 46(1):47–64

    Article  MathSciNet  MATH  Google Scholar 

  • Latouche G, Ramaswami V (1999) Introduction to matrix analytic methods in stochastic modelling., Series on statistics and applied probabilitySIAM, Philadelphia

    Book  MATH  Google Scholar 

  • Li Z, Zou C, Gong Z, Wang Z (2014) The computation of average run length and average time to signal: an overview. J Stat Comput Simul 84(8):1779–1802

    Article  MathSciNet  Google Scholar 

  • Lowry C, Montgomery D (1995) A review of multivariate control charts. IIE Trans 27(6):800–810

    Article  Google Scholar 

  • Montgomery D (2009) Statistical quality control: a modern introduction. Wiley, New York

    MATH  Google Scholar 

  • Morais M, Okhrin Y, Schmid W (2015) Quality surveillance with EWMA control charts based on exact control limits. Stat Pap 56(3):863–885

    Article  MathSciNet  MATH  Google Scholar 

  • Mukherjee P (2015) On phase II monitoring of the probability distributions of univariate continuous processes. Stat Pap 57(2):539–562

  • Neuts M (1981) Matrix-geometric solutions in stochastic models: an algorithmic approach. Johns Hopkins University Press, Baltimore

    MATH  Google Scholar 

  • Öksoy D, Boulos E, Pye L (1994) Statistical process control by the quotient of two correlated normal variables. Qual Eng 6(2):179–194

    Article  Google Scholar 

  • Page ES (1954) Continuous inspection schemes. Biometrika 41(1–2):243–257

    MathSciNet  MATH  Google Scholar 

  • Pham-Gia T, Turkkan N, Marchand E (2006) Density of the ratio of two normal random variables and applications. Commun Stat: Theory Methods 35(9):1569–1591

    Article  MathSciNet  MATH  Google Scholar 

  • Spisak A (1990) A control chart for ratios. J Qual Technol 22(1):34–37

    Google Scholar 

  • Tran KP, Castagliola P, Celano G (2015a) Monitoring the ratio of two normal variables using run rules type control charts. Int J Prod Res 54(6):1670–1688

  • Tran KP, Castagliola P, Celano G (2015b) Monitoring the ratio of two normal variables using EWMA type control charts. Qual Reliab Eng Int. doi:10.1002/qre.1918 (in press)

  • Tsai T, Yen W (2011) Exponentially weighted moving average control charts for three-level products. Stat Pap 52(2):419–429

    Article  MathSciNet  MATH  Google Scholar 

  • Woodall W, Adams B (1993) The statistical design of CUSUM charts. Qual Eng 5(4):559–570

    Article  Google Scholar 

Download references

Acknowledgments

The authors thank the anonymous referees and the editor for their valuable suggestions which helped to improve the quality of the final manuscript.

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Correspondence to Kim Phuc Tran.

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Tran, K.P., Castagliola, P. & Celano, G. Monitoring the ratio of population means of a bivariate normal distribution using CUSUM type control charts. Stat Papers 59, 387–413 (2018). https://doi.org/10.1007/s00362-016-0769-4

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  • DOI: https://doi.org/10.1007/s00362-016-0769-4

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