RANJIT K. ROY, PhD, is an internationally known consultant and trainer who has achieved recognition for his down-to-earth teaching style of Taguchi experimental design. Since 1977, he has been Adjunct Professor at Oakland University in Rochester, Michigan, and is the founder of Nutek, Inc.

"An excellent book for any practicing engineers who are interested in using Taguchi's approach in optimizing and characterizing a process. Dr. Roy's step-by-step method outlined in the book does not require the readers to have any prior statistical knowledge to understand Taguchi's approach to Design of Experiments. The book also walks you through the computer program on the CD-ROM that comes with it." - Marcus Khoo, Quality Manager, Agilent Technologies, Inc. "Per student evaluations (including my own!), Ranjit Roy is one of the best instructors that anyone is likely to meet. This is especially remarkable considering that Dr. Roy specializes in a very difficult subject: making Design of Experiments (DoE) easy to understand and accessible to everyone. His software, Qualitek 4, based upon his experience in doing real experiments and teaching other engineers to do experiments, established the benchmark in how to make this type of software useful and user friendly. While traditional classes in designed experiments spend considerable time teaching engineers how to do the mathematical analysis of these studies (yawn), Ranjit likes to teach engineers how to do experiments using software that automatically designs the experiment, analyzes the data, and prints reports (with graphics) that can immediately be shared in management or team meetings. Now Ranjit has taken about fifteen years of experience in teaching these types of classes, and has made it available to everyone in a recent book published by John Wiley & Sons, Wiley-Interscience Professional/Trade Division. This book is written for people who want to learn a method for designing and analyzing simple experiments with the goal of helping the reader apply these techniques in their own work environment. I believe this book will be particularly helpful to engineers (Black Belts or Green Belts) trying to learn the technique of designed experiments as taught in the Six Sigma process. This book is a "must have" for anyone who currently uses, or who wants to learn to use, Ranjit's software. Others will want to purchase this book for the very plentiful and helpful case studies taken from real life experiences. Dr. Roy provides resources for three key elements of the learning process: brief discussions of applicable theory, step-by-step application of the concepts, and fully functional software to use with the stories/examples in the book. Explanations of theory are simple and elegant. For example, in explaining to the reader the concept of "Degrees Of Freedom", Ranjit writes, "Degrees Of Freedom (DOF) is an indication of the amount of information contained in a data set. For example, if there are three numbers in a data set, the DOF=3-1, which indicates the amount of additional information that can be derived by taking the differences among the three numbers. Looked at in another way, if there are three people, you will need two comparisons to determine who is tallest." No wonder engineers like to take Dr. Roy's classes! Dr. Roy provides sixteen steps to learn designed experiments and apply the methods to any problem. These steps include topics such as: Dr. Taguchi's philosophy, the definition of quality and how to measure it, the logic behind experimental design analysis methods, the use of orthogonal arrays, two-level experiments, three-level experiments, Analysis of Variance (ANOVA), interactions, mixed level factors, combination designs, strategies for robust design, signal-to-noise ratios, experiments with multiple criteria, how to quantify improvement, experiment preparation and planning, and even more case studies (a special chapter of added examples in addition to the plentiful examples provided in each of the above mentioned topics). Each step is a chapter, and each chapter: starts with a learning objective, provides learning by going through examples using software, and then ends with: a "question and answer" dialogue based upon Ranjit's teaching experience, a chapter summary, additional exercises, and software solutions for these exercises. Readers will especially appreciate material in the book that is original with Ranjit himself: the development of overall evaluation criteria for studies with multiple responses, and the use of a "severity index" to quantify the strength of an interaction. The real heart of this book is the combination of software with examples. The book takes the reader through the software frame by frame, showing you where to click, what the output looks like, and how to interpret this output. The software provided with the book is fully functional with the data from the examples used in the book. However, when it comes time for the reader to do their own experiments, they are only allowed to use the portion of the software that deals with two-level experiments in an L8 orthogonal array (unless, of course, you purchase the complete software package). The software requires Windows 3.1 or higher with 32 MB RAM, 10 MB of hard drive space, a CD-ROM drive, and Microsoft PowerPoint and Word (to view additional documents). Ranjit makes it clear that this book is intended for beginners who want to get started. He only covers Taguchi's static robustness studies (even though the software is capable of dynamic studies), and tells the reader that, "As you gain application experience, you will find it necessary to refer to other books to develop clearer concepts of the mathematical treatments." Readers check assumptions in their analysis by doing a confirmation experiment to see if the result of setting factors at the perceived best levels falls within a confidence interval provided by the software. No book is perfect. Critics may say that some of the definitions are weak (for example, "system design" is defined as the "design of a product or process using special Taguchi techniques"), that some areas are too simplified (not enough emphasis on assumptions used in the analysis, no explanation of the distinction between data replication and repetition, no mention that the Cpk analysis is only applicable if the process is stable), and that in certain situations the software is weak (Dr. Roy warns the reader that the software will not correctly calculate confidence intervals if the Degrees Of Freedom are less than three, and that in some situations the software will only allow you to use an 80% confidence interval). No doubt, the biggest criticism of the book is that the reader will learn how to use many features of the software that they will not be able to later apply unless they purchase the full software package. Nevertheless, a beginner can learn designed experiments with this book, and can make a great deal of progress using L8 arrays (in fact, the technique of designed experiments is so powerful that readers may be able to purchase software for their entire company based upon the savings associated with the application of one good L8 experiment!). So, if you have ever thought about doing experiments but have never quite felt comfortable enough to get started ? get this book and get going. We have Ranjit to thank for taking the fear out of the process and providing engineers with simple explanations, examples, and software to quickly build the self-confidence needed to get real results." -Larry R. Smith, Quality and Reliability Manager, Ford Motor Company

• Preface. Acknowledgments. Symbols and Abbreviations. Introduction. Design of Experiments and the Taguchi Approach. Definition and Measurement of Quality. Common Experiments and Methods of Analysis. Experimental Design Using Orthogonal Arrays. Experimental Design with Two-Level Factors Only. Experimental Design With Three- and Four-Level Factors. Analysis of Variance. Experimental Design for Studying Factors Interaction. Experimental Design with Mixed-Level Factors. Combination Designs. Strategies for Robust Design. Analysis Using Signal-to-Noise Ratios. Results Comprising Multiple Criteria of Evaluations. Quantification of Variation Reduction and Performance Improvement. Effective Experiment Preparation and Planning. Case Studies. Appendix. What's on the Disk. Index. List of Symbols.

RANJIT K. ROY, PhD, is an internationally known consultant and trainer who has achieved recognition for his down-to-earth teaching style of Taguchi experimental design. Since 1977, he has been Adjunct Professor at Oakland University in Rochester, Michigan, and is the founder of Nutek, Inc.

"An excellent book for any practicing engineers who are interested in using Taguchi's approach in optimizing and characterizing a process. Dr. Roy's step-by-step method outlined in the book does not require the readers to have any prior statistical knowledge to understand Taguchi's approach to Design of Experiments. The book also walks you through the computer program on the CD-ROM that comes with it." - Marcus Khoo, Quality Manager, Agilent Technologies, Inc. "Per student evaluations (including my own!), Ranjit Roy is one of the best instructors that anyone is likely to meet. This is especially remarkable considering that Dr. Roy specializes in a very difficult subject: making Design of Experiments (DoE) easy to understand and accessible to everyone. His software, Qualitek 4, based upon his experience in doing real experiments and teaching other engineers to do experiments, established the benchmark in how to make this type of software useful and user friendly. While traditional classes in designed experiments spend considerable time teaching engineers how to do the mathematical analysis of these studies (yawn), Ranjit likes to teach engineers how to do experiments using software that automatically designs the experiment, analyzes the data, and prints reports (with graphics) that can immediately be shared in management or team meetings. Now Ranjit has taken about fifteen years of experience in teaching these types of classes, and has made it available to everyone in a recent book published by John Wiley & Sons, Wiley-Interscience Professional/Trade Division. This book is written for people who want to learn a method for designing and analyzing simple experiments with the goal of helping the reader apply these techniques in their own work environment. I believe this book will be particularly helpful to engineers (Black Belts or Green Belts) trying to learn the technique of designed experiments as taught in the Six Sigma process. This book is a "must have" for anyone who currently uses, or who wants to learn to use, Ranjit's software. Others will want to purchase this book for the very plentiful and helpful case studies taken from real life experiences. Dr. Roy provides resources for three key elements of the learning process: brief discussions of applicable theory, step-by-step application of the concepts, and fully functional software to use with the stories/examples in the book. Explanations of theory are simple and elegant. For example, in explaining to the reader the concept of "Degrees Of Freedom", Ranjit writes, "Degrees Of Freedom (DOF) is an indication of the amount of information contained in a data set. For example, if there are three numbers in a data set, the DOF=3-1, which indicates the amount of additional information that can be derived by taking the differences among the three numbers. Looked at in another way, if there are three people, you will need two comparisons to determine who is tallest." No wonder engineers like to take Dr. Roy's classes! Dr. Roy provides sixteen steps to learn designed experiments and apply the methods to any problem. These steps include topics such as: Dr. Taguchi's philosophy, the definition of quality and how to measure it, the logic behind experimental design analysis methods, the use of orthogonal arrays, two-level experiments, three-level experiments, Analysis of Variance (ANOVA), interactions, mixed level factors, combination designs, strategies for robust design, signal-to-noise ratios, experiments with multiple criteria, how to quantify improvement, experiment preparation and planning, and even more case studies (a special chapter of added examples in addition to the plentiful examples provided in each of the above mentioned topics). Each step is a chapter, and each chapter: starts with a learning objective, provides learning by going through examples using software, and then ends with: a "question and answer" dialogue based upon Ranjit's teaching experience, a chapter summary, additional exercises, and software solutions for these exercises. Readers will especially appreciate material in the book that is original with Ranjit himself: the development of overall evaluation criteria for studies with multiple responses, and the use of a "severity index" to quantify the strength of an interaction. The real heart of this book is the combination of software with examples. The book takes the reader through the software frame by frame, showing you where to click, what the output looks like, and how to interpret this output. The software provided with the book is fully functional with the data from the examples used in the book. However, when it comes time for the reader to do their own experiments, they are only allowed to use the portion of the software that deals with two-level experiments in an L8 orthogonal array (unless, of course, you purchase the complete software package). The software requires Windows 3.1 or higher with 32 MB RAM, 10 MB of hard drive space, a CD-ROM drive, and Microsoft PowerPoint and Word (to view additional documents). Ranjit makes it clear that this book is intended for beginners who want to get started. He only covers Taguchi's static robustness studies (even though the software is capable of dynamic studies), and tells the reader that, "As you gain application experience, you will find it necessary to refer to other books to develop clearer concepts of the mathematical treatments." Readers check assumptions in their analysis by doing a confirmation experiment to see if the result of setting factors at the perceived best levels falls within a confidence interval provided by the software. No book is perfect. Critics may say that some of the definitions are weak (for example, "system design" is defined as the "design of a product or process using special Taguchi techniques"), that some areas are too simplified (not enough emphasis on assumptions used in the analysis, no explanation of the distinction between data replication and repetition, no mention that the Cpk analysis is only applicable if the process is stable), and that in certain situations the software is weak (Dr. Roy warns the reader that the software will not correctly calculate confidence intervals if the Degrees Of Freedom are less than three, and that in some situations the software will only allow you to use an 80% confidence interval). No doubt, the biggest criticism of the book is that the reader will learn how to use many features of the software that they will not be able to later apply unless they purchase the full software package. Nevertheless, a beginner can learn designed experiments with this book, and can make a great deal of progress using L8 arrays (in fact, the technique of designed experiments is so powerful that readers may be able to purchase software for their entire company based upon the savings associated with the application of one good L8 experiment!). So, if you have ever thought about doing experiments but have never quite felt comfortable enough to get started ? get this book and get going. We have Ranjit to thank for taking the fear out of the process and providing engineers with simple explanations, examples, and software to quickly build the self-confidence needed to get real results." -Larry R. Smith, Quality and Reliability Manager, Ford Motor Company

• Preface. Acknowledgments. Symbols and Abbreviations. Introduction. Design of Experiments and the Taguchi Approach. Definition and Measurement of Quality. Common Experiments and Methods of Analysis. Experimental Design Using Orthogonal Arrays. Experimental Design with Two-Level Factors Only. Experimental Design With Three- and Four-Level Factors. Analysis of Variance. Experimental Design for Studying Factors Interaction. Experimental Design with Mixed-Level Factors. Combination Designs. Strategies for Robust Design. Analysis Using Signal-to-Noise Ratios. Results Comprising Multiple Criteria of Evaluations. Quantification of Variation Reduction and Performance Improvement. Effective Experiment Preparation and Planning. Case Studies. Appendix. What's on the Disk. Index. List of Symbols.

RANJIT K. ROY, PhD, is an internationally known consultant and trainer who has achieved recognition for his down-to-earth teaching style of Taguchi experimental design. Since 1977, he has been Adjunct Professor at Oakland University in Rochester, Michigan, and is the founder of Nutek, Inc.

"An excellent book for any practicing engineers who are interested in using Taguchi's approach in optimizing and characterizing a process. Dr. Roy's step-by-step method outlined in the book does not require the readers to have any prior statistical knowledge to understand Taguchi's approach to Design of Experiments. The book also walks you through the computer program on the CD-ROM that comes with it." - Marcus Khoo, Quality Manager, Agilent Technologies, Inc. "Per student evaluations (including my own!), Ranjit Roy is one of the best instructors that anyone is likely to meet. This is especially remarkable considering that Dr. Roy specializes in a very difficult subject: making Design of Experiments (DoE) easy to understand and accessible to everyone. His software, Qualitek 4, based upon his experience in doing real experiments and teaching other engineers to do experiments, established the benchmark in how to make this type of software useful and user friendly. While traditional classes in designed experiments spend considerable time teaching engineers how to do the mathematical analysis of these studies (yawn), Ranjit likes to teach engineers how to do experiments using software that automatically designs the experiment, analyzes the data, and prints reports (with graphics) that can immediately be shared in management or team meetings. Now Ranjit has taken about fifteen years of experience in teaching these types of classes, and has made it available to everyone in a recent book published by John Wiley & Sons, Wiley-Interscience Professional/Trade Division. This book is written for people who want to learn a method for designing and analyzing simple experiments with the goal of helping the reader apply these techniques in their own work environment. I believe this book will be particularly helpful to engineers (Black Belts or Green Belts) trying to learn the technique of designed experiments as taught in the Six Sigma process. This book is a "must have" for anyone who currently uses, or who wants to learn to use, Ranjit's software. Others will want to purchase this book for the very plentiful and helpful case studies taken from real life experiences. Dr. Roy provides resources for three key elements of the learning process: brief discussions of applicable theory, step-by-step application of the concepts, and fully functional software to use with the stories/examples in the book. Explanations of theory are simple and elegant. For example, in explaining to the reader the concept of "Degrees Of Freedom", Ranjit writes, "Degrees Of Freedom (DOF) is an indication of the amount of information contained in a data set. For example, if there are three numbers in a data set, the DOF=3-1, which indicates the amount of additional information that can be derived by taking the differences among the three numbers. Looked at in another way, if there are three people, you will need two comparisons to determine who is tallest." No wonder engineers like to take Dr. Roy's classes! Dr. Roy provides sixteen steps to learn designed experiments and apply the methods to any problem. These steps include topics such as: Dr. Taguchi's philosophy, the definition of quality and how to measure it, the logic behind experimental design analysis methods, the use of orthogonal arrays, two-level experiments, three-level experiments, Analysis of Variance (ANOVA), interactions, mixed level factors, combination designs, strategies for robust design, signal-to-noise ratios, experiments with multiple criteria, how to quantify improvement, experiment preparation and planning, and even more case studies (a special chapter of added examples in addition to the plentiful examples provided in each of the above mentioned topics). Each step is a chapter, and each chapter: starts with a learning objective, provides learning by going through examples using software, and then ends with: a "question and answer" dialogue based upon Ranjit's teaching experience, a chapter summary, additional exercises, and software solutions for these exercises. Readers will especially appreciate material in the book that is original with Ranjit himself: the development of overall evaluation criteria for studies with multiple responses, and the use of a "severity index" to quantify the strength of an interaction. The real heart of this book is the combination of software with examples. The book takes the reader through the software frame by frame, showing you where to click, what the output looks like, and how to interpret this output. The software provided with the book is fully functional with the data from the examples used in the book. However, when it comes time for the reader to do their own experiments, they are only allowed to use the portion of the software that deals with two-level experiments in an L8 orthogonal array (unless, of course, you purchase the complete software package). The software requires Windows 3.1 or higher with 32 MB RAM, 10 MB of hard drive space, a CD-ROM drive, and Microsoft PowerPoint and Word (to view additional documents). Ranjit makes it clear that this book is intended for beginners who want to get started. He only covers Taguchi's static robustness studies (even though the software is capable of dynamic studies), and tells the reader that, "As you gain application experience, you will find it necessary to refer to other books to develop clearer concepts of the mathematical treatments." Readers check assumptions in their analysis by doing a confirmation experiment to see if the result of setting factors at the perceived best levels falls within a confidence interval provided by the software. No book is perfect. Critics may say that some of the definitions are weak (for example, "system design" is defined as the "design of a product or process using special Taguchi techniques"), that some areas are too simplified (not enough emphasis on assumptions used in the analysis, no explanation of the distinction between data replication and repetition, no mention that the Cpk analysis is only applicable if the process is stable), and that in certain situations the software is weak (Dr. Roy warns the reader that the software will not correctly calculate confidence intervals if the Degrees Of Freedom are less than three, and that in some situations the software will only allow you to use an 80% confidence interval). No doubt, the biggest criticism of the book is that the reader will learn how to use many features of the software that they will not be able to later apply unless they purchase the full software package. Nevertheless, a beginner can learn designed experiments with this book, and can make a great deal of progress using L8 arrays (in fact, the technique of designed experiments is so powerful that readers may be able to purchase software for their entire company based upon the savings associated with the application of one good L8 experiment!). So, if you have ever thought about doing experiments but have never quite felt comfortable enough to get started ? get this book and get going. We have Ranjit to thank for taking the fear out of the process and providing engineers with simple explanations, examples, and software to quickly build the self-confidence needed to get real results." -Larry R. Smith, Quality and Reliability Manager, Ford Motor Company

• Preface. Acknowledgments. Symbols and Abbreviations. Introduction. Design of Experiments and the Taguchi Approach. Definition and Measurement of Quality. Common Experiments and Methods of Analysis. Experimental Design Using Orthogonal Arrays. Experimental Design with Two-Level Factors Only. Experimental Design With Three- and Four-Level Factors. Analysis of Variance. Experimental Design for Studying Factors Interaction. Experimental Design with Mixed-Level Factors. Combination Designs. Strategies for Robust Design. Analysis Using Signal-to-Noise Ratios. Results Comprising Multiple Criteria of Evaluations. Quantification of Variation Reduction and Performance Improvement. Effective Experiment Preparation and Planning. Case Studies. Appendix. What's on the Disk. Index. List of Symbols.