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From the Back Cover: Introduction to Quality Engineering is the first book with specific in-depth methods that places the responsibility of quality on everyone associated with the marketing, engineering and manufacturing of a product, and turns them all into Quality Control specialists. The book quantifies the loss due to lack of quality of a performance characteristic by directly relating it to its deviation from target performance, and shows efficient experimental and analytical techniques to minimize it. Unlike other books on quality and industrial experimentation which treat the subject specialty in a localized manner, this book encompasses all major activities of an industry, and links them together with a common objective of reducing quality loss. Chapters of the book progress smoothly and build upon the previous chapters. Each chapter introduces the subject matter, then a real life case study follows and ends with question and answer session between Dr. Taguchi and the student in a typical class. The techniques shown are powerful but easy to apply, and does not require statistical background or any other prerequisites; thus, the subject can be taught to engineers in an industry or in engineering schools.
This book presents the state-of-the-art in quality and reliability engineering from a product life-cycle standpoint. Topics in reliability include reliability models, life data analysis and modeling, design for reliability as well as accelerated life testing and reliability growth analysis, while topics in quality include design for quality, acceptance sampling and supplier selection, statistical process control, production tests such as environmental stress screening and burn-in, warranty and maintenance. The book provides comprehensive insights into two closely related subjects, and includes a wealth of examples and problems to enhance readers’ comprehension and link theory and practice. All numerical examples can be easily solved using Microsoft Excel. The book is intended for senior undergraduate and postgraduate students in related engineering and management programs such as mechanical engineering, manufacturing engineering, industrial engineering and engineering management programs, as well as for researchers and engineers in the quality and reliability fields. Dr. Renyan Jiang is a professor at the Faculty of Automotive and Mechanical Engineering, Changsha University of Science and Technology, China.
Completely revised and updated, A First Course in Quality Engineering: Integrating Statistical and Management Methods of Quality, Second Edition contains virtually all the information an engineer needs to function as a quality engineer. The authors not only break things down very simply but also give a full understanding of why each topic covered is essential to learning proper quality management. They present the information in a manner that builds a strong foundation in quality management without overwhelming readers. See what’s new in the new edition: Reflects changes in the latest revision of the ISO 9000 Standards and the Baldrige Award criteria Includes new mini-projects and examples throughout Incorporates Lean methods for reducing cycle time, increasing throughput, and reducing waste Contains increased coverage of strategic planning This text covers management and statistical methods of quality engineering in an integrative manner, unlike other books on the subject that focus primarily on one of the two areas of quality. The authors illustrate the use of quality methods with examples drawn from their consulting work, using a reader-friendly style that makes the material approachable and encourages self-study. They cover the must-know fundamentals of probability and statistics and make extensive use of computer software to illustrate the use of the computer in solving quality problems. Reorganized to make the book suitable for self study, the second edition discusses how to design Total Quality System that works. With detailed coverage of the management and statistical tools needed to make the system perform well, the book provides a useful reference for professionals who need to implement quality systems in any environment and candidates preparing for the exams to qualify as a certified quality engineer (CQE).
Lean production, has long been regarded as critical to business success in many industries. Over the last ten years, instruction in six sigma has been increasingly linked with learning about the elements of lean production. Introduction to Engineering Statistics and Lean Sigma builds on the success of its first edition (Introduction to Engineering Statistics and Six Sigma) to reflect the growing importance of the "lean sigma" hybrid. As well as providing detailed definitions and case studies of all six sigma methods, Introduction to Engineering Statistics and Lean Sigma forms one of few sources on the relationship between operations research techniques and lean sigma. Readers will be given the information necessary to determine which sigma methods to apply in which situation, and to predict why and when a particular method may not be effective. Methods covered include: • control charts and advanced control charts, • failure mode and effects analysis, • Taguchi methods, • gauge R&R, and • genetic algorithms. The second edition also greatly expands the discussion of Design For Six Sigma (DFSS), which is critical for many organizations that seek to deliver desirable products that work first time. It incorporates recently emerging formulations of DFSS from industry leaders and offers more introductory material on the design of experiments, and on two level and full factorial experiments, to help improve student intuition-building and retention. The emphasis on lean production, combined with recent methods relating to Design for Six Sigma (DFSS), makes Introduction to Engineering Statistics and Lean Sigma a practical, up-to-date resource for advanced students, educators, and practitioners.
The book presents a systematic and efficient method to design high quality / reliability and high performance products / processes at low cost. Contains case studies from diverse engineering fields to describe Robust Design / Taguchi method.Some topics covered are: orthogonal arrays, Signal-to-Noise ratios as design quality metric, computer-aided robust design techniques, and more.
Written by one of the foremost authorities on the subject, the Second Edition is completely revised to reflect the latest changes to the ASQ Body of Knowledge for the Certified Quality Engineer (CQE). This handbook covers every essential topic required by the quality engineer for day-to-day practices in planning, testing, finance, and management and thoroughly examines and defines the principles and benefits of Six Sigma management and organization. The Quality Engineering Handbook provides new and expanded sections on management systems, leadership and facilitation principles and techniques, training, customer relations, documentation systems, domestic and international standards, and more.
In the last fifty years, one man stands out as the driving force behind the quality revolution--Genichi Taguchi. Now, for the first time in one volume, Taguchi's Quality Engineering Handbook presents all the methods and beliefs that have made Taguchi one of the most respected authorities on quality engineering and management in the world. No other single volume presents the full breadth of founding beliefs behind the successful engineering practices used by today's leading companies. (Midwest).
As quality becomes an increasingly essential factor for achieving business success, building quality improvement into all stages—product planning, product design, and process design—instead of just manufacturing has also become essential. Quality Engineering: Off-Line Methods and Applications explores how to use quality engineering methods and other modern techniques to ensure design optimization at every stage. The book takes a broad approach, focusing on the user’s perspective and building a well-structured framework for the study and implementation of quality engineering. Starting with the basics, this book presents an overall picture of quality engineering. The author delineates quality engineering methods such as DOE, Taguchi, and RSM as well as computational intelligence approaches. He discusses how to use a general computational intelligence approach to improve product quality and process performance. He also provides extensive examples and case studies, numerous exercises, and a glossary of basic terms. By adopting quality engineering, the defect rate during manufacturing shows noticeable improvement, the production cost is significantly lower, and the quality and reliability of products can be enhanced. Taking an integrated approach that makes the methods of upstream quality improvement accessible, without extensive mathematical treatments, this book is both a practical reference and an excellent textbook.
This book is written primarily for engineers and researchers who use statistical robust design for quality engineering and Six Sigma, and for statisticians who wish to know about the wide range of applications of experimental design in industry. It is a valuable guide and reference material for students, managers, quality improvement specialists and other professionals interested in Taguchi's robust design methods as well as the implementation of Six Sigma. This book can also be useful to those who would like to learn about the role of Robust Design within the Six Sigma (Improve phase) methodology and Design for Six Sigma (DFSS) (Optimize) methodology. It combines classical experimental design methods with those of Taguchi's robust designs, demonstrating their prowess in DFSS and suggesting new directions for the development of statistical design and analysis.
The one resource needed to create reliable software This text offers a comprehensive and integrated approach to software quality engineering. By following the author's clear guidance, readers learn how to master the techniques to produce high-quality, reliable software, regardless of the software system's level of complexity. The first part of the publication introduces major topics in software quality engineering and presents quality planning as an integral part of the process. Providing readers with a solid foundation in key concepts and practices, the book moves on to offer in-depth coverage of software testing as a primary means to ensure software quality; alternatives for quality assurance, including defect prevention, process improvement, inspection, formal verification, fault tolerance, safety assurance, and damage control; and measurement and analysis to close the feedback loop for quality assessment and quantifiable improvement. The text's approach and style evolved from the author's hands-on experience in the classroom. All the pedagogical tools needed to facilitate quick learning are provided: * Figures and tables that clarify concepts and provide quick topic summaries * Examples that illustrate how theory is applied in real-world situations * Comprehensive bibliography that leads to in-depth discussion of specialized topics * Problem sets at the end of each chapter that test readers' knowledge This is a superior textbook for software engineering, computer science, information systems, and electrical engineering students, and a dependable reference for software and computer professionals and engineers.