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Introduction to data analysis; Distributions and their uses; Level four statistical analysis techniques.
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).
The book focuses on the introduction of the basic concepts, processes, and tools used in Lean Six Sigma. A unique feature is the detailed discussion on Design for Six Sigma aided by computer modeling and simulation. The authors present several sample projects in which Lean Six Sigma and Design for Six Sigma were used to solve engineering problems or improve processes based on their own research and development experiences in engineering design and analysis. This book is intended to be a textbook for advanced undergraduate students, graduate students in engineering, and mid-career engineering professionals. It can also be a reference book, or be used to prepare for the Six Sigma Green Belt and Black Belt certifications by organizations such as American Society for Quality.
Reflecting more than 30 years of teaching experience in the field, this guide provides engineers with an introduction to statistics and its applicability to engineering. Examples cover a wide range of engineering applications, including both chemical engineering and semiconductors. Among the topics featured are: quality assurance and statistics, continuous variables, hypothesis testing, comparative experiments, acceptance sampling, the analysis of variance, Taguchi and Orthogonal arrays. Tables, references and an index round out this work.
Statistical methods are made easier for engineers and scientists in this highly respected interdisciplinary reference. Covering a broad spectrum of statistical methods used at intermediate and advanced levels, the second edition features new sections on additional graphical tools, acceptance sampling, and the uses of new software. Matching how-to procedures to specific disciplines simplifies the application. Coverage of each statistical principle is followed by an example of its application. Users gain vital guidance on survey sampling, computer simulation, design and analysis of experiments, and more. Guidelines for organizing and managing a statistical consulting firm are included.
Now with even more examples with real data, real-world applications, and computer exercise, the Fourth Edition of this accessible text prepares you for situations you're likely to encounter as a professionakl engineer. Together with new co-authors David Goldsman and Connie Borror, William Hines and Douglas Montgomery have refined their highly effective pedagogical framework to make their text even more user friendly. This Fourth Edition also features a new chapter on statistical methods for computer situation, as well exceptionally clear statistical coverage, expanded discussions of quiality control, experimental design, and different types of interval estimation, and coverage of such special topics as nonparametric statistics, p-values in hypothetical testing, and residual analysis. Highlights of the Fourth Edition: * New examples and applications provide a real-world perspective on how engineers use probability and statistics in professional practice. * Over 600 exercises, including many new computation problems, provide opportunities for hands-on learning. * An entirely new chapter on statistical methods for computer simulation methods covers Monte Carlo experimentation, random number and variate generation, and simulation output data analysis. * New chapter organization starts with probability theory and progresses through random variables, discrete and continuous distributions, and normal distribution, before introducing statistics and data description techniques. * Each chapter starts with an introduction that describes the importance of the topic and features interesting historical information related to the topic. * End-of-chapter summaries reinforce the main topics and goals of the chapter.
A fine blend of the three disciplines, viz. quality, reliability and maintainability, this book provides a clear understanding of the concepts and discusses their applications using statistical tools and techniques. The concepts are critically assessed and explained to enable their use for management decision-making. The book describes many current topics such as six sigma, capability maturity model integration (CMMI), process data management, reliability system models, repairable system models, maintainability assessment and design and testing concepts. It is intended as a textbook for the undergraduate students of Mechanical Engineering and Production and Industrial Engineering. The book will also be useful to the postgraduate students of Applied Statistics, Quality and Reliability, and Quality and Productivity Management as well as to the management and engineering professionals. KEY FEATURES : Provides charts and plots to explain the concepts discussed. Gives an account of most recent developments. Gives illustrations of practical situations where tools can be applied immediately. Interspersed with plenty of worked-out examples to reinforce the concepts. Includes chapter-end exercises to drill the students in self-study.
In today’s global and highly competitive environment, continuous improvement in the processes and products of any field of engineering is essential for survival. This book gathers together the full range of statistical techniques required by engineers from all fields. It will assist them to gain sensible statistical feedback on how their processes or products are functioning and to give them realistic predictions of how these could be improved. The handbook will be essential reading for all engineers and engineering-connected managers who are serious about keeping their methods and products at the cutting edge of quality and competitiveness.