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Now in its 6th edition, this bestselling professional reference has helped over 100,000 engineers and scientists with the success of their experiments. Douglas Montgomery arms readers with the most effective approach for learning how to design, conduct, and analyze experiments that optimize performance in products and processes. He shows how to use statistically designed experiments to obtain information for characterization and optimization of systems, improve manufacturing processes, and design and develop new processes and products. You will also learn how to evaluate material alternatives in product design, improve the field performance, reliability, and manufacturing aspects of products, and conduct experiments effectively and efficiently. Discover how to improve the quality and efficiency of working systems with this highly-acclaimed book. This 6th Edition: Places a strong focus on the use of the computer, providing output from two software products: Minitab and DesignExpert. Presents timely, new examples as well as expanded coverage on adding runs to a fractional factorial to de-alias effects. Includes detailed discussions on how computers are currently used in the analysis and design of experiments. Offers new material on a number of important topics, including follow-up experimentation and split-plot design. Focuses even more sharply on factorial and fractional factorial design.
Real Engineering Situations, Real Engineering Data With Montgomery and Runger's best-selling engineering statistics text, you can learn how to apply statistics to real engineering situations. The text shows you how to use statistical methods to design and develop new products, and new manufacturing systems and processes. You'll gain a better understanding of how these methods are used in everyday work, and get a taste of practical engineering experience through real-world, engineering-based examples and exercises. Now revised, this Fourth Edition of Applied Statistics and Probability for Engineers features many new homework exercises, including a greater variation of problems and more computer problems. Key Features * The text treats all topics in a way that reflects today's engineering realities. In the probability chapters, the authors emphasize engineering-specific examples, rather than counting methods or artificial applications such as gambling. * Examples and exercises throughout the text use real data and real engineering situations. * Coverage of probability is lively and interesting. It is complete but concise so as not to take over the content of the entire text. * Thorough coverage of regression modeling, design of engineering experiments, and statistical process control from experts in these topics makes the book especially useful as a reference.
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Now updated and revised From the reviews of the First Edition . . . "Truly a book that can be read by practitioners...Anyone who deals with designing experiments, the statistical analysis and modeling of data, and especially product or process improvement, including optimization, should have this book as a reference." -Technometrics "An excellent book for practitioners. Ownership...is a professional necessity." -Journal of the American Statistical Association Identifying and fitting an appropriate response surface model from experimental data requires knowledge of statistical experimental design fundamentals, regression modeling techniques, and elementary optimization methods. This book integrates these three topics into a comprehensive, state-of-the-art presentation of response surface methodology (RSM). This new second edition has been substantially rewritten and updated to include new topics and material, new examples, and to more fully illustrate modern applications of RSM. The authors have made the computer a more integral part of their presentation, employing the most common and useful software packages. They bring an applied focus to the subject of RSM, emphasizing methods that are useful in industry for product and process design and development. Features include: * Coverage of two-level factorial and fractional factorial design, and empirical modeling of RSM * Optimization techniques useful in RSM, including multiple responses * Classical and modern response surface designs, including computer-generated designs * The RSM approach to robust parameter design and process robustness studies * Comprehensive treatment of mixture experiments * Revised and expanded end-of-chapter problems, an extensive reference section, and valuable technical appendices on RSM * Supported by Design-Expert software Response Surface Methodology develops the underlying theory of RSM, describes the assumptions and conditions necessary to successfully apply it, and provides comprehensive and authoritative discussion of current topics for statisticians, engineers, and students.
"In this book, you'll develop the skills and understanding you need to use basic statistics in engineering and scientific problem solving! Best-selling authors Jay Devore and Nicholas Farnum draw on real data from industry reports and articles to introduce you to statistics as it is used in real-world engineering situations. You'll find practical use of the computer, modern statistical methods, including quality and design of experiments, and graphical data analysis methods."--BOOK JACKET.Title Summary field provided by Blackwell North America, Inc. All Rights Reserved