03943cam a22003615i 4500999001700000001000900017005001700026008004100043010001700084020001800101020001500119020001500134020001800149040001300167042000800180050002100188100002700209245007100236250001700307260003800324300003200362490002200394500002800416504004100444505100100485505100701486505082602493650002503319650002603344906004503370942003203415952013403447  c30814d308141801767420201007152036.0140124s2014    enka     b    000 0 eng    a  2014931715  a9780080994178  a0080994172  a0080994199  a9780080994192  aDLCcDLC  apcc  aQA279b.A58 20141 aAntony, Jiju,eauthor.10aDesign of experiments for engineers and scientists /cJiju Antony.  a2nd edition.  aAmsterdam : bElsevier, c ©2014  ax, 208 p. :bill. ;c24 cm.0 aElsevier insights  aPrevious edition: 2003.  aIncludes bibliographical references.0 aMachine generated contents note: 1. Introduction to Industrial Experimentation -- 1.1. Introduction -- 1.2. Some Fundamental and Practical Issues in Industrial Experimentation -- 1.3. Statistical Thinking and its Role Within DOE -- Exercises -- References -- 2. Fundamentals of Design of Experiments -- 2.1. Introduction -- 2.2. Basic Principles of DOE -- 2.3. Degrees of Freedom -- 2.4. Confounding -- 2.5. Selection of Quality Characteristics for Industrial Experiments -- Exercises -- References -- 3. Understanding Key Interactions in Processes -- 3.1. Introduction -- 3.2. Alternative Method for Calculating the Two-Order Interaction Effect -- 3.3. Synergistic Interaction Versus Antagonistic Interaction -- 3.4. Scenario 1 -- 3.5. Scenario 2 -- 3.6. Scenario 3 -- Exercises -- References -- 4.A Systematic Methodology for Design of Experiments -- 4.1. Introduction -- 4.2. Barriers in the Successful Application of DOE -- 4.3.A Practical Methodology for DOE -- 4.4. Analytical Tools of DOE.0 aContents note continued: 4.5. Model Building for Predicting Response Function -- 4.6. Confidence Interval for the Mean Response -- 4.7. Statistical, Technical and Sociological Dimensions of DOE -- Exercises -- References -- 5. Screening Designs -- 5.1. Introduction -- 5.2. Geometric and Non-geometric P--B Designs -- Exercises -- References -- 6. Full Factorial Designs -- 6.1. Introduction -- 6.2. Example of a 22 Full Factorial Design -- 6.3. Example of a 23 Full Factorial Design -- 6.4. Example of a 24 Full Factorial Design -- Exercises -- References -- 7. Fractional Factorial Designs -- 7.1. Introduction -- 7.2. Construction of Half-Fractional Factorial Designs -- 7.3. Example of a 2(7--4) Factorial Design -- 7.4. An Application of 2-Level Fractional Factorial Design -- Exercises -- References -- 8. Some Useful and Practical Tips for Making Your Industrial Experiments Successful -- 8.1. Introduction -- Exercises -- References -- 9. Case Studies -- 9.1. Introduction -- 9.2. Case Studies.0 aContents note continued: References -- 10. Design of Experiments and its Applications in the Service Industry -- 10.1. Introduction to the Service Industry -- 10.2. Fundamental Differences Between the Manufacturing and Service Organisations -- 10.3. DOE in the Service Industry: Fundamental Challenges -- 10.4. Benefits of DOE in Service/Non-Manufacturing Industry -- 10.5. DOE: Case Examples from the Service Industry -- 10.6. Role of Computer Simulation Models Within DOE -- Exercises -- References -- 11. Design of Experiments and its Role Within Six Sigma -- 11.1. What is Six Sigma? -- 11.2. How Six Sigma is Different from Other Quality Improvement Initiatives of the Past -- 11.3. Who Makes Six Sigma Work? -- 11.4. Six Sigma Methodology (DMAIC Methodology) -- 11.5. DOE and its Role Within Six Sigma -- Exercises. 0aExperimental design. 0aResearch, Industrial.  a0bibccorigresd2encipf20gy-gencatlg  2lcccBOOKShQA279 .A58 2014  00102lcc4070aMUCbMUCcGENd2020-10-07eCo-operate campus g6201.00l0oQA279 .A58 2014p23351r2020-10-21w2020-10-07yBOOKS