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2016 | 26 | nr 4 | 5--19
Tytuł artykułu

A Control Chart Using Belief Information for a Gamma Distribution

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The design of a control chart has been presented using a belief estimator by assuming that the quantitative characteristic of interest follows the gamma distribution. The authors present the structure of the proposed chart and derive the average run lengths for in-control and a shifted process. The average run lengths for various specified parameters have been reported. The efficiency of the proposed chart has been compared to existing control charts. The application of the proposed chart is illustrated with the help of simulated data. (original abstract)
Rocznik
Tom
26
Numer
Strony
5--19
Opis fizyczny
Twórcy
  • King Abdulaziz University (KAU), Jeddah, Saudi Arabia
  • University of Veterinary and Animal Sciences, Lahore, Pakistan
  • POSTECH, Pohang, Republic of Korea
Bibliografia
  • [1] SHEU S.H., LIN T.C., The generally weighted moving average control chart for detecting small shifts in the process mean, Quality Eng., 2003, 16 (2), 209.
  • [2] SHEWHART W.A., Economic control of quality of manufactured product, Vol. 509, ASQ Quality Press, D. Van Nostrand Company, Inc., 1931.
  • [3] PAGE E., Continuous inspection schemes, Biometrika, 1954, 100.
  • [4] NENES G., TAGARAS G., An economic comparison of CUSUM and Shewhart charts, IIE Trans., 2007, 40 (2), 133.
  • [5] DE VARGAS V.D.C.C., DIAS LOPES L.F., MENDONÇA SOUZA D.A., Comparative study of the performance of the CuSum and EWMA control charts, Comp. Ind. Eng., 2004, 46 (4), 707.
  • [6] HUNTER J.S., The exponentially weighted moving average, J. Quality Techn., 1986, 18 (4), 203.
  • [7] LOWRY C.A., CHAMP C.W., WOODALL W.H., The performance of control charts for monitoring process variation, Comm. Stat. Sim. Comp., 1995, 24 (2), 409.
  • [8] CROWDER S.V., A simple method for studying run-length distributions of exponentially weighted moving average charts, Technomet., 1987, 29 (4), 401.
  • [9] XIE M., GOH T.N., RANJAN P., Some effective control chart procedures for reliability monitoring, Rel. Eng. Syst. Safety, 2002, 77 (2), 143.
  • [10] JEARKPAPORN D., MONTGOMERY D.C., RUNGER G.C., BORROR C.M., Process monitoring for correlated gamma distributed data using generalized linear model-based control charts, Qual. Rel. Eng. Int., 2003, 19 (6), 477.
  • [11] HAN D., TSUNG F., A generalized EWMA control chart and its comparison with the optimal EWMA, CUSUM and GLR schemes, Ann. Stat., 2004, 32 (1), 316.
  • [12] LIU P.-H., CHEN F.-L., Process capability analysis of non-normal process data using the Burr XII distribution, Int. J. Adv. Manuf. Techn., 2006, 27 (9-10), 975.
  • [13] MONTGOMERY D.C., Introduction to Statistical Quality Control, Wiley, 2007.
  • [14] ZHANG C., XIE M., LIU J.Y., GOH T.N., A control chart for the gamma distribution as a model of time between events, Int. J. Prod. Res., 2007, 45 (23), 5649.
  • [15] ZHANG S., WU Z., Monitoring the process mean and variance using a weighted loss function CUSUM scheme with variable sampling intervals, IIE Trans., 2006, 38 (4), 377.
  • [16] RIAZ M., Monitoring process mean level using auxiliary information, Stat. Nederland., 2008, 62 (4), 458.
  • [17] YEH A.B., MEGRATH R.N., SEMBOWER M.A., SHEN Q., EWMA control charts for monitoring high-yield processes based on non-transformed observations, Int. J. Prod. Res., 2008, 46 (20), 5679.
  • [18] ASLAM M., AZAM M., JUN C.-H., A new exponentially weighted moving average sign chart using repetitive sampling, J. Proc. Control, 2014, 24 (7), 1149.
  • [19] ASLAM, M., YEN C.-H., CHANG C.-H., JUN C.-H., Multiple dependent state variable sampling plans with process loss consideration, Int. J. Adv. Manuf. Techn., 2014, 71 (5-8), 1337.
  • [20] ASLAM M., AZAM M., KHAN N., JUN C.-H., A control chart for an exponential distribution using multiple dependent state sampling, Qual. Quant., 2015, 49 (2), 455.
  • [21] GÜLBAY M., KAHRAMAN C., An alternative approach to fuzzy control charts: Direct fuzzy approach. Information sciences, Infor. Sci., 2007, 177 (6), 1463.
  • [22] FALLAH NEZHAD M.S., AKHAVAN NIAKI S.T., A new monitoring design for uni-variate statistical quality control charts, Inf. Sci., 2010, 180 (6), 1051.
  • [23] SANTIAGO E., SMITH J., Control charts based on the exponential distribution: Adapting runs rules for the t chart, Qual. Eng., 2013, 25 (2), 85.
  • [24] LUCAS J.M., SACCUCCI M.S., Exponentially weighted moving average control schemes: properties and enhancements, Technometrics, 1990, 32 (1), 1.
  • [25] CASTAGLIOLA P., CELANO G., FICHERA D.S., Monitoring process variability using EWMA, [in:] H. Pham (Ed.), Springer Handbook of Engineering Statistics, Springer, 2006, 291-325.
  • [26] WU Z., ZHANG S., WANG P., A CUSUM scheme with variable sample sizes and sampling intervals for monitoring the process mean and variance, Qual. Rel. Eng. Int., 2007, 23 (2), 157.
  • [27] ASLAM M., KHAN N., AZAM N., JUN C.-H., Designing of a new monitoring t-chart using repetitive sampling, Inf. Sci., 2014, 269, 210.
  • [28] ASLAM M., KHAN N., JUN C.-H., Designing of a control chart using belief statistic for exponential distribution, Comm. Stat. Sim. Comp., 2016 (accepted).
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171456441

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