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Attribute np control charts using resampling systems for monitoring non-conforming items using exponentiated half logistic distribution

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
An attribute np control chart has been designed using resampling systems for monitoring non- -conforming items under exponentiated half-logistic distribution. We suppose that lifetime follows exponentiated half-logistic distribution. For the proposed control charts, the optimal parameters and control limits have been obtained. The operational formulas for in-control and out of control average run lengths (ARLs) have been derived. Control constants are established by considering the target in-control ARL at a normal process. The extensive ARL tables are reported for various parameters and shifted values of process parameters. The performance of the proposed control chart is evaluated with several existing charts with regard to ARLs, which empower the presented chart and prove far better for timely detection of assignable causes. A wide range of tables, a real-life example, and simulation study for RGS and MDS are given for a better understanding of the problem.
Rocznik
Strony
115--143
Opis fizyczny
Bibliogr. 23 poz., rys.
Twórcy
  • National College of Business Administration and Economics, Lahore 54660, Pakistan
  • Department of Statistics and Computer Science, University of Veterinary and Animal Sciences, Lahore 54000, Pakistan
  • Department of Statistics, Faculty of Science, King Abdulaziz University, Jeddah 21551, Saudi Arabia
  • Higher Education Department, Government of the Punjab, Lahore 54000, Pakistan
Bibliografia
  • [1] SHERMAN R.E., Design and evaluation of a RGS plan, Technometrics, 1965, 7, 11–21.
  • [2] BALAMURALI S., JUN C.-H., Repetitive group sampling procedure for variables inspection, J. Appl. Stat., 2006, 33, 327–338.
  • [3] AHMAD L., ASLAM M.,JUN C.-H., Designing of X-bar control charts based on process capability index using repetitive sampling, Trans. Inst. Measure. Control, 2014, 36, 367–374.
  • [4] ASLAM M., AZAM M., JUN C.-H., New attributes and variables control charts under repetitive sampling, Ind. Eng. Manage. Syst., 2014, 13, 101–106.
  • [5] ASLAM M., KHAN N., AZAM M., JUN C.-H., Designing of a new monitoring t-chart using repetitive sampling, Inf. Sci., 2014, 269, 210–216.
  • [6] RAO G., A control chart for time truncated life tests using exponentiated half logistic distribution, Appl. Math. Inf. Sci., 2018, 12, 125–131.
  • [7] WORTHAM A.,BAKER R., Multiple deferred state sampling inspection, Int. J. Prod. Res., 1976, 14, 719–731.
  • [8] 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, 1337–1343.
  • [9] ASLAM M., KHAN N., JUN C.-H., A multiple dependent state control chart based on double control limits, Res. J. Appl. Sci. Eng. Techn., 2014, 7, 4490–4493.
  • [10] RAO G.S., NAIDU C., Acceptance sampling plans for percentiles based on the exponentiated half logistic distribution, Appl. Appl. Math., 2014, 9, 39–53.
  • [11] ASLAM M., Time truncated attribute control chart for the Weibull distribution using MDS, Comm. Stat.-Sim. Comp., 2019, 48, 1219–1228.
  • [12] JEYADURGA P., BALAMURALI S., ASLAM M., Design of an attribute np control chart for process monitoring based on repetitive group sampling under truncated life tests, Comm. Stat.-Theory Meth., 2018, 47, 5934–5955.
  • [13] MUDHOLKAR G.S., SRIVASTAVA D.K., Exponentiated Weibull family for analyzing bathtub failure-rate data, IEEE Trans. Rel., 1993, 42, 299–302.
  • [14] CORDEIRO G.M., ALIZADEH M., ORTEGA E.M., The exponentiated half-logistic family of distributions: Properties and applications, J. Prob. Stat., 2014, 2014.
  • [15] SEO J.-I., KANG S.-B., Notes on the exponentiated half logistic distribution, Appl. Math. Model., 2015, 39, 6491–6500.
  • [16] ELGARHY M., HAQ M., OZEL G., A new exponentiated extended family of distributions with applications, Gazi University J. Sci., 2017, 30, 101–115.
  • [17] USMAN R.M., HAQ M., TALIB J., Kumaraswamy half-logistic distribution: properties and applications, J. Stat. Appl. Prob., 2017, 6, 597–609.
  • [18] ANWAR M., BIBI A., The half-logistic generalized Weibull distribution, J. Prob. Stat., 2018, 2018.
  • [19] MONTGOMERY D.C., Introduction to statistical quality control, Wiley, 2007.
  • [20] HINKLEY D., On quick choice of power transformation, J. Royal Stat. Soc., Series C, 1977, 26, 67–69.
  • [21] SEO J.-I., LEE H.-J., KAN S.-B., Estimation for generalized half logistic distribution based on records, J. Korean Data Inf. Sci. Soc., 2012, 23, 1249–1257.
  • [22] AZIMI R., SARIKHANBAGLU F.A., Bayes and empirical bayes estimators based on generalized half logistic records data, Journal of Statistics Appl. Prob., 2014, 3, 145?.
  • [23] TORABI H.,BAGHERI F., Estimation of parameters for an extended generalized half logistic distribution based on complete and censored data, J. Iranian Stat. Soc., 2010, 9, 171–195.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-77ea2738-b78f-4efe-8487-5d9a4b2866ae
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