LEADER 05302nam 2200661Ia 450 001 9910780448403321 005 20200520144314.0 010 $a1-280-96404-9 010 $a9786610964048 010 $a0-08-046995-7 035 $a(CKB)111090529102654 035 $a(EBL)286669 035 $a(OCoLC)171114036 035 $a(SSID)ssj0000137257 035 $a(PQKBManifestationID)11150315 035 $a(PQKBTitleCode)TC0000137257 035 $a(PQKBWorkID)10111265 035 $a(PQKB)11147142 035 $a(PQKBManifestationID)16031710 035 $a(PQKB)22954399 035 $a(Au-PeEL)EBL286669 035 $a(CaPaEBR)ebr10166962 035 $a(CaONFJC)MIL96404 035 $a(MiAaPQ)EBC286669 035 $a(EXLCZ)99111090529102654 100 $a20040407d2003 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aDesign of experiments for engineers and scientists$b[electronic resource] /$fJiju Antony 210 $aOxford $cButterworth-Heinemann$d2003 215 $a1 online resource (165 p.) 300 $aDescription based upon print version of record. 311 $a1-4175-0546-X 311 $a0-7506-4709-4 320 $aIncludes bibliographical references and index. 327 $aCover; Contents; Preface; Acknowledgements; Introduction to industrial experimentation; Introduction; Some fundamental and practical issues in industrial experimentation; Summary; Exercises; References; Fundamentals of Design of Experiments; Introduction; Basic principles of Design of Experiments; Randomization; Replication; Blocking; Degrees of freedom; Confounding; Design resolution; Metrology considerations for industrial designed experiments; Measurement system capability; Some tips for the development of a measurement system 327 $aSelection of quality characteristics for industrial experimentsExercises; References; Understanding key interactions in processes; Introduction; Alternative method for calculating the two order interaction effect; Synergistic interaction vs antagonistic interaction; Scenario 1; Scenario 2; Summary; Exercises; References; A systematic methodology for Design of Experiments; Introduction; Barriers in the successful application of DOE; A practical methodology for DOE; Planning phase; Designing phase; Conducting phase; Analysing phase; Analytical tools of DOE; Main effects plot; Interactions plots 327 $aCube plotsPareto plot of factor effects; Normal Probability Plot of factor effects; Normal Probability Plot of residuals; Response surface plots and regression models; Model building for predicting response function; Confidence interval for the mean response; Summary; Exercises; References; Screening designs; Introduction; Geometric and non-geometric P-B designs; Summary; Exercises; References; Full factorial designs; Introduction; Example of a 22 full factorial design; Objective 1: Determination of main/interaction effects which influence mean plating thickness 327 $aObjective 2: Determination of main/interaction effects which influence variability in plating thicknessObjective 4: How to achieve a target plating thickness of 120 units?; Example of a 23 full factorial design; Objective 1: To identify the significant main/ interaction effects which affect the process yield; Objective 2: To identify the significant main/ interaction effects which affect the variability in process yield; Objective 3: What is the optimal process condition?; Example of a 24 full factorial design; Objective 1: Which of the main/interaction effects affect mean crack length? 327 $aObjective 2: Which of the main/interaction effects affect variability in crack length?Objective 3: What is the optimal process condition to minimize mean crack length?; Summary; Exercises; References; Fractional factorial designs; Introduction; Construction of half-fractional factorial designs; Example of a 2(7 4) factorial design 76; An application of 2-level fractional factorial design; Example of a 2(5 - 1) factorial design; Objective 1: To identify the factors which influence the mean free height 327 $aObjective 2: To identify the factors which affect variability in the free height of leaf springs 330 $aThe tools and technique used in the Design of Experiments (DOE) have been proved successful in meeting the challenge of continuous improvement over the last 15 years. However, research has shown that applications of these techniques in small and medium-sized manufacturing companies are limited due to a lack of statistical knowledge required for their effective implementation. Although many books have been written in this subject, they are mainly by statisticians, for statisticians and not appropriate for engineers.Design of Experiments for Engineers and Scientists overcomes the 606 $aExperimental design 606 $aResearch, Industrial 615 0$aExperimental design. 615 0$aResearch, Industrial. 676 $a658.5 700 $aAntony$b Jiju$0627430 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910780448403321 996 $aDesign of experiments for engineers and scientists$91212910 997 $aUNINA