Download or read book Understanding Industrial Experimentation written by Donald J. Wheeler and published by S P C Press. This book was released on 1988 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Design of Experiments for Engineers and Scientists written by Jiju Antony and published by Elsevier. This book was released on 2023-06-02 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: This third edition of Design of Experiments for Engineers and Scientists adds to the tried and trusted tools that were successful in so many engineering organizations with new coverage of design of experiments (DoE) in the service sector. Case studies are updated throughout, and new ones are added on dentistry, higher education, and utilities. Although many books have been written on DoE for statisticians, this book overcomes the challenges a wider audience faces in using statistics by using easy-to-read graphical tools. Readers will find the concepts in this book both familiar and easy to understand, and users will soon be able to apply them in their work or research. This classic book is essential reading for engineers and scientists from all disciplines tackling all kinds of product and process quality problems and will be an ideal resource for students of this topic. Written in nonstatistical language, the book is an essential and accessible text for scientists and engineers who want to learn how to use DoE Explains why teaching DoE techniques in the improvement phase of Six Sigma is an important part of problem-solving methodology New edition includes two new chapters on DoE for services as well as case studies illustrating its wider application in the service industry

Download or read book Industrial Design of Experiments written by Sammy Shina and published by Springer Nature. This book was released on 2022 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides the tools, techniques, and industry examples needed for the successful implementation of design of experiments (DoE) in engineering and manufacturing applications. It contains a high-level engineering analysis of key issues in the design, development, and successful analysis of industrial DoE, focusing on the design aspect of the experiment and then on interpreting the results. Statistical analysis is shown without formula derivation, and readers are directed as to the meaning of each term in the statistical analysis. Industrial Design of Experiments: A Case Study Approach for Design and Process Optimization is designed for graduate-level DoE, engineering design, and general statistical courses, as well as professional education and certification classes. Practicing engineers and managers working in multidisciplinary product development will find it to be an invaluable reference that provides all the information needed to accomplish a successful DoE. Presents classical versus Taguchi DoE methodologies as well as techniques developed by the author for successful DoE; Offers a step-wise approach to DoE optimization and interpretation of results; Includes industrial case studies, worked examples and detailed solutions to problems.

Download or read book Applications of Statistics to Industrial Experimentation written by Cuthbert Daniel and published by John Wiley & Sons. This book was released on 2009-09-25 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: Other volumes in the Wiley Series in Probability and MathematicalStatistics, Ralph A. Bradley, J. Stuart Hunter, David G. Kendall,& Geoffrey S. Watson, Advisory Editors Statistical Models inApplied Science Karl V. Bury Of direct interest to engineers andapplied scientists, this book presents general principles ofstatistics and specific distribution methods and models. Prominentdistribution properties and methods that are useful over a widerange of applications are covered in detail. The strengths andweaknesses of the distributional models are fully described, givingthe reader a firm, intuitive approach to the selection of the modelmost appropriate to the problem at hand. 1975 656 pp. FittingEquations To Data Computer Analysis of Multifactor Data forScientists and Engineers Cuthbert Daniel & Fred S. Wood Withthe assistance of John W. Gorman The purpose of this book is tohelp the serious data analyst, scientist, or engineer with acomputer to: recognize the strengths and limitations of his data;test the assumptions implicit in the least squares methods used tofit the data; select appropriate forms of the variables; judgewhich combinations of variables are most influential; and state theconditions under which the fitted equations are applicable.Throughout, mathematics is kept at the level of college algebra.1971 342 pp. Methods for Statistical Analysis of Reliability AndLife Data Nancy R. Mann, Ray E. Schafer & Nozer D. SingpurwallaThis book introduces failure models commonly used in reliabilityanalysis, and presents the most useful methods for analyzing thelife data of these models. Highlights include: material onaccelerated life testing; a comprehensive treatment of estimationand hypothesis testing; a critical survey of methods forsystem-reliability confidence bonds; and methods for simulation oflife data and for testing fit. 1974 564 pp.

Download or read book Screening written by Angela Dean and published by Springer Science & Business Media. This book was released on 2006-07-28 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: The process of discovery in science and technology may require investigation of a large number of features, such as factors, genes or molecules. In Screening, statistically designed experiments and analyses of the resulting data sets are used to identify efficiently the few features that determine key properties of the system under study. This book brings together accounts by leading international experts that are essential reading for those working in fields such as industrial quality improvement, engineering research and development, genetic and medical screening, drug discovery, and computer simulation of manufacturing systems or economic models. Our aim is to promote cross-fertilization of ideas and methods through detailed explanations, a variety of examples and extensive references. Topics cover both physical and computer simulated experiments. They include screening methods for detecting factors that affect the value of a response or its variability, and for choosing between various different response models. Screening for disease in blood samples, for genes linked to a disease and for new compounds in the search for effective drugs are also described. Statistical techniques include Bayesian and frequentist methods of data analysis, algorithmic methods for both the design and analysis of experiments, and the construction of fractional factorial designs and orthogonal arrays. The material is accessible to graduate and research statisticians, and to engineers and chemists with a working knowledge of statistical ideas and techniques. It will be of interest to practitioners and researchers who wish to learn about useful methodologies from within their own area as well as methodologies that can be translated from one area to another.

Download or read book Quality Improvement Through Planned Experimentation 3E PB written by Ronald Moen and published by McGraw Hill Professional. This book was released on 2012-06-05 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: The latest experimental design techniques for quality improvement "The methods taught in this book are a major contribution to statistical methods as an aid to engineers, as well as to those in industry, education, or government who are trying to understand the meaning of fi gures derived from comparisons or experiments." -- W. EDWARDS DEMING Co-written by three recipients of the Deming Medal awarded by the American Society for Quality (ASQ), Quality Improvement through Planned Experimentation, Third Edition discusses the principles and methodologies for planning and conducting experiments to improve products, processes, or systems. Fully revised with up-to-date case studies and incorporating new software, this authoritative guide fosters the sequential building of knowledge essential for implementing effective improvements. End-of-chapter exercises reinforce what you've learned, and forms for designing planned experiments help you to integrate the methods in the book into your daily work. The methods of planned experimentation provide an opportunity to better meet the needs of customers, reduce costs, and increase productivity by effecting verifiably beneficial changes. COVERAGE INCLUDES: * Improvement of quality * Principles for design and analysis of planned experiments * Experiments with one factor * Experiments with more than one factor * Reducing the size of experiments * Evaluating sources of variation * Sequential experimentation * Using a time series response variable * Designs with factors at more than two levels * Applications in health care * New product design NEW: Study-it software available for download!

Download or read book Constructive Experiments in Industrial Cooperation Between Employers and Employees written by Academy of Political Science (U.S.) and published by . This book was released on 1922 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Experiments written by C. F. Jeff Wu and published by John Wiley & Sons. This book was released on 2011-09-20 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition: "If you . . . want an up-to-date, definitive reference written by authors who have contributed much to this field, then this book is an essential addition to your library." —Journal of the American Statistical Association Fully updated to reflect the major progress in the use of statistically designed experiments for product and process improvement, Experiments, Second Edition introduces some of the newest discoveries—and sheds further light on existing ones—on the design and analysis of experiments and their applications in system optimization, robustness, and treatment comparison. Maintaining the same easy-to-follow style as the previous edition while also including modern updates, this book continues to present a new and integrated system of experimental design and analysis that can be applied across various fields of research including engineering, medicine, and the physical sciences. The authors modernize accepted methodologies while refining many cutting-edge topics including robust parameter design, reliability improvement, analysis of non-normal data, analysis of experiments with complex aliasing, multilevel designs, minimum aberration designs, and orthogonal arrays. Along with a new chapter that focuses on regression analysis, the Second Edition features expanded and new coverage of additional topics, including: Expected mean squares and sample size determination One-way and two-way ANOVA with random effects Split-plot designs ANOVA treatment of factorial effects Response surface modeling for related factors Drawing on examples from their combined years of working with industrial clients, the authors present many cutting-edge topics in a single, easily accessible source. Extensive case studies, including goals, data, and experimental designs, are also included, and the book's data sets can be found on a related FTP site, along with additional supplemental material. Chapter summaries provide a succinct outline of discussed methods, and extensive appendices direct readers to resources for further study. Experiments, Second Edition is an excellent book for design of experiments courses at the upper-undergraduate and graduate levels. It is also a valuable resource for practicing engineers and statisticians.

Download or read book A Comprehensive Guide to Factorial Two Level Experimentation written by Robert Mee and published by Springer Science & Business Media. This book was released on 2009-06-23 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains the most comprehensive coverage available anywhere for two-level factorial designs. The re-analysis of 50 published examples serves as a how-to guide for analysis of the many types of full factorial and fractional factorial designs. By focusing on two-level designs, this book is accessible to a wide audience of practitioners who use planned experiments.

Download or read book Experimental Quality written by Jiju Antony and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Improving the quality of products and manufacturing processes at low cost is an economic and technological challenge to industrial engineers and managers alike. In today's business world, the implementation of experimental design techniques often falls short of the mark due to a lack of statistical knowledge on the part of engineers and managers in their analyses of manufacturing process quality problems. This timely book aims to fill this gap in the statistical knowledge required by engineers to solve manufacturing quality problems by using Taguchi experimental design methodology. The book increases awareness of strategic methodology through real-life case studies, providing valuable information for both academics and professionals with no prior knowledge of the theory of probability and statistics. Experimental Quality: Provides a unique framework to help engineers and managers address quality problems and use strategic design methodology. Offers detailed case studies illustrating the implementation of experimental design theory. Is easily accessible without prior knowledge or understanding of probability and statistics. This book provides an excellent resource for both academic and industrial environments, and will prove invaluable to practising industrial engineers, quality engineers and engineering managers from all disciplines.

Download or read book Successful Industrial Experimentation written by Brett Kyle and published by VCH Publishers. This book was released on 1995 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to improving industrial processes and products through simple quality improvement techniques and experimental design methodology. Addressed to chemists, biologists, engineers and others with a limited understanding of statistics, explains the fundamentals of a sound experimental approach to problem solving that incorporates valid statistical analysis. Covers data collection, flow diagrams, Pareto analysis, and cause and effect diagrams. Annotation copyright by Book News, Inc., Portland, OR

Download or read book Optimization and Industrial Experimentation written by William E. Biles and published by John Wiley & Sons. This book was released on 1980-03-10 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: Combines new developments in numerical optimization with statistical and experimental methods. Discusses the use of statistical methods to develop mathematical models; search methods for single-variable and multiple-variable optimization as well as classical and numerical techniques directly applicable in response surface methodology; and procedures for optimizing systems experimentally.

Download or read book Design of Experiments for Engineers and Scientists written by Jiju Antony and published by Elsevier. This book was released on 2003-09-05 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 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 problem of statistics by taking a unique approach using graphical tools. The same outcomes and conclusions are reached as by those using statistical methods and readers will find the concepts in this book both familiar and easy to understand. The book treats Planning, Communication, Engineering, Teamwork and Statistical Skills in separate chapters and then combines these skills through the use of many industrial case studies. Design of Experiments forms part of the suite of tools used in Six Sigma. Key features: * Provides essential DOE techniques for process improvement initiatives * Introduces simple graphical techniques as an alternative to advanced statistical methods – reducing time taken to design and develop prototypes, reducing time to reach the market * Case studies place DOE techniques in the context of different industry sectors * An excellent resource for the Six Sigma training program This book will be useful to engineers and scientists from all disciplines tackling all kinds of manufacturing, product and process quality problems and will be an ideal resource for students of this topic. Dr Jiju Anthony is Senior Teaching Fellow at the International Manufacturing Unit at Warwick University. He is also a trainer and consultant in DOE and has worked as such for a number of companies including Motorola, Vickers, Procter and Gamble, Nokia, Bosch and a large number of SMEs. * Provides essential DOE techniques for process improvement initiatives * Introduces simple graphical techniques as an alternative to advanced statistical methods - reducing time taken to design and conduct tests * Case studies place DOE techniques in the context of different industry sectors

Download or read book Industrial Experimentation written by Kenneth Alexander Brownlee and published by . This book was released on 1953 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Optimal Design of Experiments written by Peter Goos and published by John Wiley & Sons. This book was released on 2011-06-28 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This is an engaging and informative book on the modern practice of experimental design. The authors' writing style is entertaining, the consulting dialogs are extremely enjoyable, and the technical material is presented brilliantly but not overwhelmingly. The book is a joy to read. Everyone who practices or teaches DOE should read this book." - Douglas C. Montgomery, Regents Professor, Department of Industrial Engineering, Arizona State University "It's been said: 'Design for the experiment, don't experiment for the design.' This book ably demonstrates this notion by showing how tailor-made, optimal designs can be effectively employed to meet a client's actual needs. It should be required reading for anyone interested in using the design of experiments in industrial settings." —Christopher J. Nachtsheim, Frank A Donaldson Chair in Operations Management, Carlson School of Management, University of Minnesota This book demonstrates the utility of the computer-aided optimal design approach using real industrial examples. These examples address questions such as the following: How can I do screening inexpensively if I have dozens of factors to investigate? What can I do if I have day-to-day variability and I can only perform 3 runs a day? How can I do RSM cost effectively if I have categorical factors? How can I design and analyze experiments when there is a factor that can only be changed a few times over the study? How can I include both ingredients in a mixture and processing factors in the same study? How can I design an experiment if there are many factor combinations that are impossible to run? How can I make sure that a time trend due to warming up of equipment does not affect the conclusions from a study? How can I take into account batch information in when designing experiments involving multiple batches? How can I add runs to a botched experiment to resolve ambiguities? While answering these questions the book also shows how to evaluate and compare designs. This allows researchers to make sensible trade-offs between the cost of experimentation and the amount of information they obtain.

Download or read book CAD 3D Modeling Engineering Analysis and Prototype Experimentation written by Jeremy Zheng Li and published by Springer. This book was released on 2014-08-26 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: This succinct book focuses on computer aided design (CAD), 3-D modeling, and engineering analysis and the ways they can be applied effectively in research and industrial sectors including aerospace, defense, automotive, and consumer products. These efficient tools, deployed for R&D in the laboratory and the field, perform efficiently three-dimensional modeling of finished products, render complex geometrical product designs, facilitate structural analysis and optimal product design, produce graphic and engineering drawings, and generate production documentation. Written with an eye toward green energy installations and novel manufacturing facilities, this concise volume enables scientific researchers and engineering professionals to learn design techniques, control existing and complex issues, proficiently use CAD tools, visualize technical fundamentals, and gain analytic and technical skills. This book also: · Equips practitioners and researchers to handle powerful tools for engineering design and analysis using many detailed illustrations · Emphasizes important engineering design principles in introducing readers to a range of techniques · Includes tutorials providing readers with appropriate scaffolding to accelerate their learning process · Adopts a product development, cost-consideration perspective through the book’s many examples

Download or read book Experimentation for Engineers written by David Sweet and published by Simon and Schuster. This book was released on 2023-03-21 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimize the performance of your systems with practical experiments used by engineers in the world’s most competitive industries. In Experimentation for Engineers: From A/B testing to Bayesian optimization you will learn how to: Design, run, and analyze an A/B test Break the "feedback loops" caused by periodic retraining of ML models Increase experimentation rate with multi-armed bandits Tune multiple parameters experimentally with Bayesian optimization Clearly define business metrics used for decision-making Identify and avoid the common pitfalls of experimentation Experimentation for Engineers: From A/B testing to Bayesian optimization is a toolbox of techniques for evaluating new features and fine-tuning parameters. You’ll start with a deep dive into methods like A/B testing, and then graduate to advanced techniques used to measure performance in industries such as finance and social media. Learn how to evaluate the changes you make to your system and ensure that your testing doesn’t undermine revenue or other business metrics. By the time you’re done, you’ll be able to seamlessly deploy experiments in production while avoiding common pitfalls. About the technology Does my software really work? Did my changes make things better or worse? Should I trade features for performance? Experimentation is the only way to answer questions like these. This unique book reveals sophisticated experimentation practices developed and proven in the world’s most competitive industries that will help you enhance machine learning systems, software applications, and quantitative trading solutions. About the book Experimentation for Engineers: From A/B testing to Bayesian optimization delivers a toolbox of processes for optimizing software systems. You’ll start by learning the limits of A/B testing, and then graduate to advanced experimentation strategies that take advantage of machine learning and probabilistic methods. The skills you’ll master in this practical guide will help you minimize the costs of experimentation and quickly reveal which approaches and features deliver the best business results. What's inside Design, run, and analyze an A/B test Break the “feedback loops” caused by periodic retraining of ML models Increase experimentation rate with multi-armed bandits Tune multiple parameters experimentally with Bayesian optimization About the reader For ML and software engineers looking to extract the most value from their systems. Examples in Python and NumPy. About the author David Sweet has worked as a quantitative trader at GETCO and a machine learning engineer at Instagram. He teaches in the AI and Data Science master's programs at Yeshiva University. Table of Contents 1 Optimizing systems by experiment 2 A/B testing: Evaluating a modification to your system 3 Multi-armed bandits: Maximizing business metrics while experimenting 4 Response surface methodology: Optimizing continuous parameters 5 Contextual bandits: Making targeted decisions 6 Bayesian optimization: Automating experimental optimization 7 Managing business metrics 8 Practical considerations