LEADER 04772nam 2200673 450 001 9910138960203321 005 20210526143450.0 010 $a1-118-84195-6 010 $a1-118-84200-6 010 $a1-118-84194-8 035 $a(CKB)2550000001198368 035 $a(EBL)1603266 035 $a(SSID)ssj0001113304 035 $a(PQKBManifestationID)11615198 035 $a(PQKBTitleCode)TC0001113304 035 $a(PQKBWorkID)11167384 035 $a(PQKB)10644448 035 $a(OCoLC)874157779 035 $a(MiAaPQ)EBC1603266 035 $a(DLC) 2013051306 035 $a(Au-PeEL)EBL1603266 035 $a(CaPaEBR)ebr10833758 035 $a(CaONFJC)MIL571624 035 $a(OCoLC)867001356 035 $a(PPN)19191195X 035 $a(EXLCZ)992550000001198368 100 $a20140214h20142014 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aStatistical robust design $ean industrial perspective /$fMagnus Arner 210 1$aChichester, England :$cWiley,$d2014. 210 4$dİ2014 215 $a1 online resource (246 p.) 300 $aDescription based upon print version of record. 311 $a1-306-40373-1 311 $a1-118-62503-X 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aStatistical Robust Design; Contents; Preface; 1 What is robust design?; 1.1 The importance of small variation; 1.2 Variance reduction; 1.3 Variation propagation; 1.4 Discussion; 1.4.1 Limitations; 1.4.2 The outline of this book; Exercises; 2 DOE for robust design, part 1; 2.1 Introduction; 2.1.1 Noise factors; 2.1.2 Control factors; 2.1.3 Control-by-noise interactions; 2.2 Combined arrays: An example from the packaging industry; 2.2.1 The experimental array; 2.2.2 Factor effect plots; 2.2.3 Analytical analysis and statistical significance; 2.2.4 Some additional comments on the plotting 327 $a2.3 Dispersion effectsExercises; Reference; 3 Noise and control factors; 3.1 Introduction to noise factors; 3.1.1 Categories of noise; 3.2 Finding the important noise factors; 3.2.1 Relating noise to failure modes; 3.2.2 Reducing the number of noise factors; 3.3 How to include noise in a designed experiment; 3.3.1 Compounding of noise factors; 3.3.2 How to include noise in experimentation; 3.3.3 Process parameters; 3.4 Control factors; Exercises; References; 4 Response, signal, and P diagrams; 4.1 The idea of signal and response; 4.1.1 Two situations; 4.2 Ideal functions and P diagrams 327 $a4.2.1 Noise or signal factor4.2.2 Control or signal factor; 4.2.3 The scope; 4.3 The signal; 4.3.1 Including a signal in a designed experiment; Exercises; 5 DOE for robust design, part 2; 5.1 Combined and crossed arrays; 5.1.1 Classical DOE versus DOE for robust design; 5.1.2 The structure of inner and outer arrays; 5.2 Including a signal in a designed experiment; 5.2.1 Combined arrays with a signal; 5.2.2 Inner and outer arrays with a signal; 5.3 Crossed arrays versus combined arrays; 5.3.1 Differences in factor aliasing; 5.4 Crossed arrays and split-plot designs 327 $a8 Mathematics of robust design8.1 Notational system; 8.2 The objective function; 8.2.1 Multidimensional problems; 8.2.2 Optimization in the presence of a signal; 8.2.3 Matrix formulation; 8.2.4 Pareto optimality; 8.3 ANOVA for robust design; 8.3.1 Traditional ANOVA; 8.3.2 Functional ANOVA; 8.3.3 Sensitivity indices; Exercises; References; 9 Design and analysis of computer experiments; 9.1 Overview of computer experiments; 9.1.1 Robust design; 9.2 Experimental arrays for computer experiments; 9.2.1 Screening designs; 9.2.2 Space filling designs; 9.2.3 Latin hypercubes 327 $a9.2.4 Latin hypercube designs and alphabetical optimality criteria 330 $aRobust Design is an important topic in many areas of the manufacturing industry, there is little on the market that provides adequate coverage. This book deals with the statistical theory of how to design products to be robust against random variation in ""noise"". It adopts a practice-oriented approach to robust design, digressing from the traditional Taguchi approach. Examples featured are taken from an industrial setting to illustrate how to make use of statistics to identify robust design solutions. 606 $aIndustrial design$xStatistical methods 606 $aRobust statistics 615 0$aIndustrial design$xStatistical methods. 615 0$aRobust statistics. 676 $a745.2 700 $aArner$b Magnus$0956008 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910138960203321 996 $aStatistical robust design$92163906 997 $aUNINA LEADER 01494nam 2200457 450 001 9910812945603321 005 20230803024342.0 010 $a1-78084-274-0 035 $a(CKB)2560000000261777 035 $a(MiAaPQ)EBC5092459 035 $a(Au-PeEL)EBL5092459 035 $a(CaPaEBR)ebr11451916 035 $a(OCoLC)861789759 035 $a(EXLCZ)992560000000261777 100 $a20171108h20132013 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 00$aAdvances in the treatment of chronic myeloid leukemia /$feditors, Giuseppe Saglio, University of Turin, Italy, Carmen Fava, University of Turin, Italy 210 1$aLondon, England :$cFuture Medicine Ltd,$d2013. 210 4$dİ2013 215 $a1 online resource (131 pages) $cillustrations, tables 311 $a1-78084-275-9 311 $a1-78084-273-2 320 $aIncludes bibliographical references at the end of each chapters and index. 606 $aChronic myeloid leukemia 606 $aChronic myeloid leukemia$xTreatment 615 0$aChronic myeloid leukemia. 615 0$aChronic myeloid leukemia$xTreatment. 676 $a616.99419 702 $aSaglio$b Giuseppe 702 $aFava$b Carmen 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910812945603321 996 $aAdvances in the treatment of chronic myeloid leukemia$93952637 997 $aUNINA