Handbook of Statistical Methods in Manufacturing PDF Download

Author: Richard Barrett Clements
Publisher:
ISBN:
Category : Business & Economics
Languages : en
Pages : 418

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Book Description

Author: Ken Yale
Publisher: Elsevier
ISBN: 0124166458
Category : Mathematics
Languages : en
Pages : 824

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Book Description
Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. - Includes input by practitioners for practitioners - Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models - Contains practical advice from successful real-world implementations - Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions - Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications

Author: David .C. Drain
Publisher: CRC Press
ISBN: 9780412127014
Category : Business & Economics
Languages : en
Pages : 342

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Book Description
Clear and organized, this handbook shows engineers how to apply advanced statistical and experimental design methods to improve industrial and manufacturing processes. Throughout the text, concepts are developed in the context of industrial examples, and the use of software is made readily accessible to promote a better comprehension though graphical and statistical analysis. Using a variety of pedagogical techniques and high-quality graphics, Handbook of Experimental Methods for Process Improvement provides an intuitive understanding of the field, enabling engineers to apply the methods discussed to practical applications.

Author: David C. Drain
Publisher: Springer
ISBN: 9781461560265
Category : Technology & Engineering
Languages : en
Pages : 317

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Book Description
This book was written to provide working engineers and engineering students with the statistical tools they must understand to improve manufacturing processes. Statistical principles are illustrated with authentic manufacturing process ex amples from the semiconductor industry, a practice that enables experienced en gineers to build upon existing knowledge to learn new skills, and which introduces students to a fascinating industry. The first book in this series, Statistical Methods For Industrial Process Control, gives background on the industry, and provides statistical understanding prerequisite to applying the methods in this text. This text emphasizes the application of statistical tools, rather than statistical the ory. Modem advances in statistical software have made tedious computations and formula memorization unnecessary, so engineers with knowledge of a few statisti cal tools can competently practice statistics within the context of their profession. Software use is demonstrated throughout the book to promote better under standing through graphical and statistical analysis. A statistical software appendix gives example Statistical Analysis System (SAS)l programs sufficient to perform 2 the analyses in the text. Some examples are shown with Minitab as well. Review problems at the end of each chapter give readers a chance to deepen their understanding. Answers to selected problems can be found at the end of the book. lSAS is a trademark of SAS Institute Inc., SAS Campus Drive, Cary, NC 27513. 2Minitab is a trademark of Minitab, Inc., 3081 Enterprise Drive, State College, PA 16801.

Author: Angela Dean
Publisher: CRC Press
ISBN: 146650434X
Category : Mathematics
Languages : en
Pages : 946

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Book Description
This carefully edited collection synthesizes the state of the art in the theory and applications of designed experiments and their analyses. It provides a detailed overview of the tools required for the optimal design of experiments and their analyses. The handbook covers many recent advances in the field, including designs for nonlinear models and algorithms applicable to a wide variety of design problems. It also explores the extensive use of experimental designs in marketing, the pharmaceutical industry, engineering and other areas.

Author: Hoang Pham
Publisher: Springer Science & Business Media
ISBN: 1852338067
Category : Business & Economics
Languages : en
Pages : 1135

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Book Description
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.

Author: Wayne A. Taylor
Publisher:
ISBN: 9780963512291
Category :
Languages : en
Pages : 0

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Book Description

Author: Anand M. Joglekar
Publisher: John Wiley & Sons
ISBN: 0470584122
Category : Science
Languages : en
Pages : 283

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Book Description
HELPS YOU FULLY LEVERAGE STATISTICAL METHODS TO IMPROVE INDUSTRIAL PERFORMANCE Industrial Statistics guides you through ten practical statistical methods that have broad applications in many different industries for enhancing research, product design, process design, validation, manufacturing, and continuous improvement. As you progress through the book, you'll discover some valuable methods that are currently underutilized in industry as well as other methods that are often not used correctly. With twenty-five years of teaching and consulting experience, author Anand Joglekar has helped a diverse group of companies reduce costs, accelerate product development, and improve operations through the effective implementation of statistical methods. Based on his experience working with both clients and students, Dr. Joglekar focuses on real-world problem-solving. For each statistical method, the book: Presents the most important underlying concepts clearly and succinctly Minimizes mathematical details that can be delegated to a computer Illustrates applications with numerous practical examples Offers a "Questions to Ask" section at the end of each chapter to assist you with implementation The last chapter consists of 100 practical questions followed by their answers. If you're already familiar with statistical methods, you may want to take the test first to determine which methods to focus on. By helping readers fully leverage statistical methods to improve industrial performance, this book becomes an ideal reference and self-study guide for scientists, engineers, managers and other technical professionals across a wide range of industries. In addition, its clear explanations and examples make it highly suited as a textbook for undergraduate and graduate courses in statistics.

Author: Peter C. Meier
Publisher: John Wiley & Sons
ISBN: 0471726117
Category : Science
Languages : en
Pages : 452

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Book Description
This new edition of a successful, bestselling book continues to provide you with practical information on the use of statistical methods for solving real-world problems in complex industrial environments. Complete with examples from the chemical and pharmaceutical laboratory and manufacturing areas, this thoroughly updated book clearly demonstrates how to obtain reliable results by choosing the most appropriate experimental design and data evaluation methods. Unlike other books on the subject, Statistical Methods in Analytical Chemistry, Second Edition presents and solves problems in the context of a comprehensive decision-making process under GMP rules: Would you recommend the destruction of a $100,000 batch of product if one of four repeat determinations barely fails the specification limit? How would you prevent this from happening in the first place? Are you sure the calculator you are using is telling the truth? To help you control these situations, the new edition: * Covers univariate, bivariate, and multivariate data * Features case studies from the pharmaceutical and chemical industries demonstrating typical problems analysts encounter and the techniques used to solve them * Offers information on ancillary techniques, including a short introduction to optimization, exploratory data analysis, smoothing and computer simulation, and recapitulation of error propagation * Boasts numerous Excel files and compiled Visual Basic programs-no statistical table lookups required! * Uses Monte Carlo simulation to illustrate the variability inherent in statistically indistinguishable data sets Statistical Methods in Analytical Chemistry, Second Edition is an excellent, one-of-a-kind resource for laboratory scientists and engineers and project managers who need to assess data reliability; QC staff, regulators, and customers who want to frame realistic requirements and specifications; as well as educators looking for real-life experiments and advanced students in chemistry and pharmaceutical science. From the reviews of Statistical Methods in Analytical Chemistry, First Edition: "This book is extremely valuable. The authors supply many very useful programs along with their source code. Thus, the user can check the authenticity of the result and gain a greater understanding of the algorithm from the code. It should be on the bookshelf of every analytical chemist."-Applied Spectroscopy "The authors have compiled an interesting collection of data to illustrate the application of statistical methods . . . including calibrating, setting detection limits, analyzing ANOVA data, analyzing stability data, and determining the influence of error propagation."-Clinical Chemistry "The examples are taken from a chemical/pharmaceutical environment, but serve as convenient vehicles for the discussion of when to use which test, and how to make sense out of the results. While practical use of statistics is the major concern, it is put into perspective, and the reader is urged to use plausibility checks."-Journal of Chemical Education "The discussion of univariate statistical tests is one of the more thorough I have seen in this type of book . . . The treatment of linear regression is also thorough, and a complete set of equations for uncertainty in the results is presented . . . The bibliography is extensive and will serve as a valuable resource for those seeking more information on virtually any topic covered in the book."-Journal of American Chemical Society "This book treats the application of statistics to analytical chemistry in a very practical manner. [It] integrates PC computing power, testing programs, and analytical know-how in the context of good manufacturing practice/good laboratory practice (GMP/GLP) . . .The book is of value in many fields of analytical chemistry and should be available in all relevant libraries."-Chemometrics and Intelligent Laboratory Systems

Author: Mary Gibbons Natrella
Publisher: Courier Corporation
ISBN: 0486154556
Category : Mathematics
Languages : en
Pages : 562

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Book Description
A handbook for those seeking engineering information and quantitative data for designing, developing, constructing, and testing equipment. Covers the planning of experiments, the analyzing of extreme-value data; and more. 1966 edition. Index. Includes 52 figures and 76 tables.