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Designed primarily as a text for the undergraduate and postgraduate students of industrial engineering, chemical engineering, production engineering, mechanical engineering, and quality engineering and management, it covers fundamentals as well as advanced concepts of Design of Experiments. The text is written in a way that helps students to independently design industrial experiments and to analyze for the inferences. Written in an easy-to-read style, it discusses different experimental design techniques such as completely randomized design, randomized complete block design and Latin square design. Besides this, the book also covers 22, 23, and 3n factorial experiments; two-stage, three-stage and mixed design with nested factors and factorial factors; different methods of orthogonal array design; and multivariate analysis of variance (MANOVA) for one-way MANOVA and factorial MANOVA. Key Features Case Studies to illustrate the concepts and techniques Chapter end questions on prototype reality problems Yates algorithm for 2n factorial experiments Answers to Selected Questions Table of Contents Preface 1. Introduction 2. Motivation For Using Analysis of Variance 3. Simple Designs of Anova 4. Complete Factorial Experiment 5. Experimental Designs With At Least One Random Factor 6. Nested Design 7. Confounded Design 8. Fractional Factorial Design 9. Split Plot Design 10. Regression Approach 11. Response Surface Methodology 12. Orthogonal Arrays 13. Robust Parameter Design 14. Grey Relational Analysis 15. Multivariate Analysis of Variance (Manova) Appendices References Answers To Selected Questions Index