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Economic statistical design for x-bar control charts under non-normal distributed data with Weibull in-control time

  • Theoretical Paper
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Journal of the Operational Research Society

Abstract

This paper proposes an approach which simultaneously considers the properties of cost and quality based on the Burr distribution to determine three parameters (including sample size, sampling interval between successive samples, and the control limits) when an x-bar chart monitors a manufacturing process with Weibull failure characteristic and non-normal data. Also, the cost model of Banerjee and Rahim (1988) is used as the objective function, and the probability density function of the Burr distribution is applied to derive the statistical constraints of economic statistical design of the x-bar control charts for non-normal data. The example of Banerjee and Rahim (1988) is adopted to indicate the solution procedure and sensitivity analyses. Meanwhile, the design parameters of the x-bar control charts can be obtained through the grid search method. The results show that an increase of skewness coefficient (α3) results in a slight decrease for sample size (n), but is robust to the control limit width (L). Also, an increase of kurtosis coefficient (α4) leads to a wider control limit width.

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References

  • Al-Oraini HA and Rahim MA (2003). Economic statistical design of X̄ control charts for systems with Gamma (λ,2) in-control times . J Appl Stat 30: 397–409.

    Google Scholar 

  • Baker KR (1971). Two process models in economic design of anX̄chart . AIIE Trans 3: 257–263.

    Article  Google Scholar 

  • Banerjee PK and Rahim MA (1988). Economic design of X̄ control charts under Weibull shock models . Technometrics 30(4): 407–414.

    Google Scholar 

  • Burr IW (1942). Cumulative frequency functions . Annal Math Stat 13: 215–232.

    Article  Google Scholar 

  • Chen HF and Cheng YY (2007). Non-normality effects on the economic-statistical design ofX̄charts with Weibull in-control time . Eur J Opl Res 176(2): 986–998.

    Article  Google Scholar 

  • Chen YK (2003). An evolutionary economic-statistical design for VSIX̄control charts under non-normality . Int J Adv Manuf Technol 22: 602–610.

    Article  Google Scholar 

  • Chou CY, Chen CH and Liu HR (2000). Economic-statistical design ofX̄charts for non-normal data by considering quality loss . J Appl Stat 27(8): 939–951.

    Article  Google Scholar 

  • Chou CY, Chen CH and Liu HR (2001). Economic design ofX̄charts for non-normally correlated data . Int J Prod Res 39(9): 1931–1941.

    Article  Google Scholar 

  • Chou CY, Chen CH, Liu HR and Huang XR (2003). Economic-statistical design of multivariate control charts for monitoring the mean vector and covariance matrix . J Loss Prev Process Indust 16: 9–18.

    Article  Google Scholar 

  • Duncan AJ (1956). The economic design ofX̄charts used to maintain current control of a process . J Am Stat Assoc 51: 228–242.

    Google Scholar 

  • Gibra IN (1971). Economically optimal determination of the economic design of anX̄control chart . Mngt Sci 17: 635–646.

    Article  Google Scholar 

  • Goel AL and Wu SM (1968). An algorithm for the determination of the economic design ofX̄ charts based on Duncan's model . J Am Stat Assoc 63: 304–320.

    Google Scholar 

  • Ho C and Case KE (1994). Economic design of control charts: A literature review for 1981–1991 . J Qual Technol 26: 1–78.

    Google Scholar 

  • Hu PW (1984). Economic model of X control chart under non-Poisson process shift. Abstract, TIMS/ORSA Joint National Meeting, San Francisco, May, 87, 14–16.

  • Knappenberger HA and Grandage AH (1969). Minimum cost quality control test . AIIE Trans 1: 24–32.

    Article  Google Scholar 

  • Lorenzen TJ and Vance LC (1986). The economic design of control charts: A unified approach . Technometrics 28: 3–10.

    Article  Google Scholar 

  • McWilliams TP (1989). Economic control chart designs and the in-control time distribution: A sensitivity study . J of Qual Technol 21: 103–110.

    Google Scholar 

  • McWilliams TP (1994). Economic, statistical, and economic-statistical X̄ chart designs . J Qual Technol 26: 227–238.

    Google Scholar 

  • McWilliams TP and Saniga EM (2001). Economic-statistical design of X̄ and R or X̄ and S charts . J Qual Technol 33: 234–241.

    Google Scholar 

  • Montgomery DC (1980). The economic design of control charts: A review and literature survey . J Qual Technol 12: 75–87.

    Google Scholar 

  • Montgomery DC, Trong JC, Cochran JK and Lawence FP (1995). Statistical constrained economic design of EWMA control chart . J Qual Technol 27: 250–256.

    Google Scholar 

  • Otha H and Rahim MA (1997). A dynamic economic model for an X̄-control chart design . IIE Trans 29(6): 481–486.

    Google Scholar 

  • Parkhideh B and Case KE (1989). The economic design of a dynamic X̄-control chart . IIE Trans 21: 313–323.

    Article  Google Scholar 

  • Rahim MA (1985). Economic model of X̄ chart under non-normality and measurement errors . Comput Opns Res 12(3): 291–299.

    Article  Google Scholar 

  • Rahim MA (1993). Economic design of X̄ control charts assuming Weibull distribution in-control times . J Qual Technol 25(4): 296–305.

    Google Scholar 

  • Rahim MA (1994). Joint determination of production quantity, inspection schedule, and control chart design . IIE Trans 26(6): 2–11.

    Article  Google Scholar 

  • Rahim MA and Banerjee PK (1993). A generalized economic model for the economic design of X̄ control charts for production systems with increasing failure rate and early replacement . Naval Res Logist 40(6): 787–809.

    Article  Google Scholar 

  • Rahim MA and Ben-Daya M (1998). A generalized economic model for joint determination of production run, inspection schedule, and control chart design . Int J Prod Res 36(1): 277–289.

    Article  Google Scholar 

  • Rahim MA and Costa AFB (2000). Joint economic design of X̄ and R charts under Weibull shock models . Int J Prod Res 38(13): 2871–2889.

    Article  Google Scholar 

  • Saniga EM (1989). Economic statistical control chart designs with an application to X̄ and R charts . Technometrics 31(3): 313–320.

    Google Scholar 

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

    Google Scholar 

  • Woodall WH (1985). The statistic design of quality control charts . Technometrics 28: 408–409.

    Article  Google Scholar 

  • Yourstone SA and Zimmer WJ (1992). Non-normality and the design of control charts for averages . Decis Sci 23: 1099–1113.

    Article  Google Scholar 

  • Zhang G and Berardi V (1997). Economic statistical design of X̄ control chart for systems with Weibull in-control times . Comput Indust Eng 32: 575–586.

    Article  Google Scholar 

  • Zimmer WJ and Burr IW (1963). Variables sampling plans based on non-normal populations . Indust Qual Control 21: 18–36.

    Google Scholar 

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Chen, F., Yeh, C. Economic statistical design for x-bar control charts under non-normal distributed data with Weibull in-control time. J Oper Res Soc 62, 750–759 (2011). https://doi.org/10.1057/jors.2010.36

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