LEADER 03648nam 22005655 450 001 9910383837403321 005 20251203070356.0 010 $a3-030-25081-4 024 7 $a10.1007/978-3-030-25081-2 035 $a(CKB)4100000010673895 035 $a(DE-He213)978-3-030-25081-2 035 $a(MiAaPQ)EBC6142246 035 $a(PPN)243228023 035 $a(EXLCZ)994100000010673895 100 $a20200319d2020 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDistribution-Free Methods for Statistical Process Monitoring and Control /$fedited by Markos V. Koutras, Ioannis S. Triantafyllou 205 $a1st ed. 2020. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020. 215 $a1 online resource (IX, 257 p. 53 illus., 17 illus. in color.) 311 08$a3-030-25080-6 320 $aIncludes bibliographical references. 327 $aAn Overview of Nonparametric Control Charts -- Distribution-free Control Charts for Monitoring the Location Parameter -- Nonparametric Control Charts for Monitoring the Dispersion Parameter -- Bivariate Nonparametric Control Charts -- Exponentially Weighted Moving Average Control Charts based on Ranks -- Cumulative Sum Control Charts based on Ranks -- Nonparametric Control Charts based on Order Statistics -- The Run-Length Distribution of Nonparametric Control Charts -- Distribution-free Control Charts for Joint Monitoring Location and Scale -- Distribution-free Phase II Control Charts for Monitoring Continuous Process. 330 $aThis book explores nonparametric statistical process control. It provides an up-to-date overview of nonparametric Shewhart-type univariate control charts, and reviews the recent literature on nonparametric charts, particularly multivariate schemes. Further, it discusses observations tied to the monitored population quantile, focusing on the Shewhart Sign chart. The book also addresses the issue of practically assuming the normality and the independence when a process is statistically monitored, and examines in detail change-point analysis-based distribution-free control charts designed for Phase I applications. Moreover, it introduces six distribution-free EWMA schemes for simultaneously monitoring the location and scale parameters of a univariate continuous process, and establishes two nonparametric Shewhart-type control charts based on order statistics with signaling runs-type rules. Lastly, the book proposes novel and effective method for early disease detection. 606 $aIndustrial Management 606 $aStatistics 606 $aInformation technology$xManagement 606 $aIndustrial Management 606 $aStatistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences 606 $aBusiness Process Management 615 0$aIndustrial Management. 615 0$aStatistics. 615 0$aInformation technology$xManagement. 615 14$aIndustrial Management. 615 24$aStatistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences. 615 24$aBusiness Process Management. 676 $a658.562015195 702 $aKoutras$b Markos V$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aTriantafyllou$b Ioannis S$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910383837403321 996 $aDistribution-Free Methods for Statistical Process Monitoring and Control$92509759 997 $aUNINA