MARC Record from marc_columbia

LEADER: 04243fam a22003974a 4500
001 3382244
005 20221020061154.0
008 020416t20022002maua b 001 0 eng
010 $a 2002066117
020 $a1402070748
035 $a(OCoLC)49626400
035 $a(OCoLC)ocm49626400
035 $9AVF3356CU
035 $a(NNC)3382244
035 $a3382244
040 $aDLC$cDLC$dDLC$dOrLoB-B
042 $apcc
050 00 $aTS156$b.X54 2002
082 00 $a658.5/62$221
100 1 $aXie, M.$q(Min)$0http://id.loc.gov/authorities/names/n2002010626
245 10 $aStatistical models and control charts for high-quality processes /$cby M. Xie, T.N. Goh, V. Kuralmani.
260 $aBoston :$bKluwer Academic Publishers,$c[2002], ©2002.
300 $axiv, 276 pages :$billustrations ;$c24 cm
336 $atext$btxt$2rdacontent
337 $aunmediated$bn$2rdamedia
504 $aIncludes bibliographical references (p. [263]-274) and index.
505 00 $g1.$tIntroduction -- $g1.1.$tBasics of statistical process control -- $g1.2.$tInadequacies of traditional attribute charts -- $g1.3.$tNeed for quality improvement -- $g1.4.$tCommon probability distributions in SPC -- $g2.$tControl Charts with Probability Limits -- $g2.1.$tUse of probability limits -- $g2.2.$tSetting up a control chart based on probability limits -- $g2.3.$tProbability limits for improvement detection -- $g2.4.$tLimitations with probability limits -- $g3.$tCumulative Count of Conforming (CCC) chart -- $g3.1.$tThe basic idea -- $g3.2.$tSetting up the CCC chart -- $g3.3.$tDecision-making related to CCC chart -- $g3.4.$tCCC chart for grouped measurement -- $g3.5.$tSome comparisons with 3-sigma limits -- $g3.6.$tCumulative quantity control (CQC) chart -- $g4.$tProcess Improvement Detection -- $g4.1.$tPotential for process improvement -- $g4.2.$tUsing CCC chart for process improvement -- $g5.$tModified Implementation of Geometric Chart --
505 80 $g5.1.$tOptimum limits for maximum average run length -- $g5.2.$tChart based on transformations -- $g5.3.$tA conditional decision procedure -- $g5.4.$tEffects of inspection errors -- $g5.5.$tEffects of estimated control limits -- $g6.$tSome Extensions to the Geometric Model -- $g6.1.$tNegative binomial control chart -- $g6.2.$tModified Poisson model -- $g6.3.$tA Markov model for dependent counts -- $g6.4.$tA model for correlated attribute processes -- $g6.5.$tSome issues for further research -- $g7.$tCUSUM and EWMA Procedures -- $g7.1.$tGeneral CUSUM procedure -- $g7.2.$tCUSUM with CCC data -- $g7.3.$tBasics of EWMA charts -- $g7.4.$tEWMA with CCC data -- $g8.$tMonitoring of Multiple Process Characteristics -- $g8.1.$tNeed and approaches for multiple characteristics -- $g8.2.$tMultivariate np (Mnp) by weighted average -- $g8.3.$tA chart with multinomial distribution -- $g8.4.$tSome issues for further research -- $g9.$tEconomic Design of Geometric Chart --
505 80 $g9.1.$tThe Lorenzen and Vance model for economic design -- $g9.2.$tEconomic design of CCC chart -- $g9.3.$tEconomic-statistical design of CCC chart -- $g9.4.$tSome further extensions -- $g10.$tMonitoring and Adjustment of Trended Processes -- $g10.1.$tAdjustment for process improvement -- $g10.2.$tInterpretation of traditional Shewhart chart -- $g10.3.$tModification of process capability indices -- $g10.4.$tCost consideration and decision making.
520 1 $a"Many examples, charts, and procedures, are presented throughout the book; and references are provided for those interested in exploring the details. A number of questions and issues are posed for further investigations. Researchers and students may find many ideas in this book useful in their academic work, as a foundation is laid for the exploration of many further theoretical and practical issues."--BOOK JACKET.
650 0 $aProduction management$xQuality control$xStatistical methods.
650 0 $aQuality assurance$xStatistical methods.
700 1 $aGoh, T. N.$q(Thong Ngee)$0http://id.loc.gov/authorities/names/n2002010621
700 1 $aKuralmani, V.$q(Vellaisamy)$0http://id.loc.gov/authorities/names/n2002010616
856 41 $3Table of contents$uhttp://www.loc.gov/catdir/toc/fy031/2002066117.html
852 00 $boff,eng$hTS156$i.X54 2002