› › Introduction To Statistical Quality Control 7e Wiley E Text Reg Card

Introduction to Statistical Quality Control

Author : Christina M. Mastrangelo

Publisher : Wiley

Page : 244 pages

File Size : 30,52 MB

Release : 1991

Category : Business & Economics

ISBN :

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Book Description

Revised and expanded, this Second Edition continues to explore the modern practice of statistical quality control, providing comprehensive coverage of the subject from basic principles to state-of-the-art concepts and applications. The objective is to give the reader a thorough grounding in the principles of statistical quality control and a basis for applying those principles in a wide variety of both product and nonproduct situations. Divided into four parts, it contains numerous changes, including a more detailed discussion of the basic SPC problem-solving tools and two new case studies, expanded treatment on variable control charts with new examples, a chapter devoted entirely to cumulative-sum control charts and exponentially-weighted, moving-average control charts, and a new section on process improvement with designed experiments.



Introduction to Statistical Quality Control

Author : Douglas C. Montgomery

Publisher : John Wiley & Sons

Page : 773 pages

File Size : 43,45 MB

Release : 2019-12-30

Category : Einführung

ISBN : 1119657113

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Book Description

"Once solely the domain of engineers, quality control has become a vital business operation used to increase productivity and secure competitive advantage. Introduction to Statistical Quality Control offers a detailed presentation of the modern statistical methods for quality control and improvement. Thorough coverage of statistical process control (SPC) demonstrates the efficacy of statistically-oriented experiments in the context of process characterization, optimization, and acceptance sampling, while examination of the implementation process provides context to real-world applications. Emphasis on Six Sigma DMAIC (Define, Measure, Analyze, Improve and Control) provides a strategic problem-solving framework that can be applied across a variety of disciplines.Adopting a balanced approach to traditional and modern methods, this text includes coverage of SQC techniques in both industrial and non-manufacturing settings, providing fundamental knowledge to students of engineering, statistics, business, and management sciences.A strong pedagogical toolset, including multiple practice problems, real-world data sets and examples, provides students with a solid base of conceptual and practical knowledge."--



Statistical Quality Control

Author : Bhisham C. Gupta

Publisher : John Wiley & Sons

Page : 400 pages

File Size : 14,66 MB

Release : 2021-07-23

Category : Technology & Engineering

ISBN : 1119671728

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Book Description

STATISTICAL QUALITY CONTROL Provides a basic understanding of statistical quality control (SQC) and demonstrates how to apply the techniques of SQC to improve the quality of products in various sectors This book introduces Statistical Quality Control and the elements of Six Sigma Methodology, illustrating the widespread applications that both have for a multitude of areas, including manufacturing, finance, transportation, and more. It places emphasis on both the theory and application of various SQC techniques and offers a large number of examples using data encountered in real life situations to support each theoretical concept. Statistical Quality Control: Using MINITAB, R, JMP and Python begins with a brief discussion of the different types of data encountered in various fields of statistical applications and introduces graphical and numerical tools needed to conduct preliminary analysis of the data. It then discusses the basic concept of statistical quality control (SQC) and Six Sigma Methodology and examines the different types of sampling methods encountered when sampling schemes are used to study certain populations. The book also covers Phase 1 Control Charts for variables and attributes; Phase II Control Charts to detect small shifts; the various types of Process Capability Indices (CPI); certain aspects of Measurement System Analysis (MSA); various aspects of PRE-control; and more. This helpful guide also Focuses on the learning and understanding of statistical quality control for second and third year undergraduates and practitioners in the field Discusses aspects of Six Sigma Methodology Teaches readers to use MINITAB, R, JMP and Python to create and analyze charts Requires no previous knowledge of statistical theory Is supplemented by an instructor-only book companion site featuring data sets and a solutions manual to all problems, as well as a student book companion site that includes data sets and a solutions manual to all odd-numbered problems Statistical Quality Control: Using MINITAB, R, JMP and Python is an excellent book for students studying engineering, statistics, management studies, and other related fields and who are interested in learning various techniques of statistical quality control. It also serves as a desk reference for practitioners who work to improve quality in various sectors, such as manufacturing, service, transportation, medical, oil, and financial institutions. It‘s also useful for those who use Six Sigma techniques to improve the quality of products in such areas.



Statistical Method from the Viewpoint of Quality Control

Author : Walter Andrew Shewhart

Publisher : Courier Corporation

Page : 218 pages

File Size : 40,2 MB

Release : 1986-01-01

Category : Mathematics

ISBN : 9780486652320

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Book Description

Important text offers lucid explanation of how to regulate variables and maintain control over statistics in order to achieve quality control over manufactured products, crops and data. Topics include statistical control, establishing limits of variability, measurements of physical properties and constants, and specification of accuracy and precision. First inexpensive paperback edition.



Statistical Methods for Reliability Data

Author : William Q. Meeker

Publisher : John Wiley & Sons

Page : 708 pages

File Size : 32,7 MB

Release : 2022-01-24

Category : Technology & Engineering

ISBN : 1118594487

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Book Description

An authoritative guide to the most recent advances in statistical methods for quantifying reliability Statistical Methods for Reliability Data, Second Edition (SMRD2) is an essential guide to the most widely used and recently developed statistical methods for reliability data analysis and reliability test planning. Written by three experts in the area, SMRD2 updates and extends the long- established statistical techniques and shows how to apply powerful graphical, numerical, and simulation-based methods to a range of applications in reliability. SMRD2 is a comprehensive resource that describes maximum likelihood and Bayesian methods for solving practical problems that arise in product reliability and similar areas of application. SMRD2 illustrates methods with numerous applications and all the data sets are available on the book’s website. Also, SMRD2 contains an extensive collection of exercises that will enhance its use as a course textbook. The SMRD2's website contains valuable resources, including R packages, Stan model codes, presentation slides, technical notes, information about commercial software for reliability data analysis, and csv files for the 93 data sets used in the book's examples and exercises. The importance of statistical methods in the area of engineering reliability continues to grow and SMRD2 offers an updated guide for, exploring, modeling, and drawing conclusions from reliability data. SMRD2 features: Contains a wealth of information on modern methods and techniques for reliability data analysis Offers discussions on the practical problem-solving power of various Bayesian inference methods Provides examples of Bayesian data analysis performed using the R interface to the Stan system based on Stan models that are available on the book's website Includes helpful technical-problem and data-analysis exercise sets at the end of every chapter Presents illustrative computer graphics that highlight data, results of analyses, and technical concepts Written for engineers and statisticians in industry and academia, Statistical Methods for Reliability Data, Second Edition offers an authoritative guide to this important topic.



Applied Statistics and Probability for Engineers

Author : Douglas C. Montgomery

Publisher : Wiley

Page : 0 pages

File Size : 10,76 MB

Release : 2005-09-02

Category : Technology & Engineering

ISBN : 9780471735564

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Book Description

* More Motivation - A completely revised chapter 1 gets students motivated right from the beginning. * Revised Probability Topics - The authors have revised and enhanced probability topics to promote even easier understanding. * Chapter Reorganization - Chapters on hypothesis testing and confidence intervals have been reorganized and rewritten. There is now expanded treatment of confidence intervals, prediction intervals, and tolerance intervals. * Real Engineering Applications - Treatment of all topics is oriented towards real engineering applications. In the probability chapters, the authors do not emphasize counting methods or artificial applications such as gambling. * Real Data, Real Engineering Situations - Examples and exercises throughout text use real data and real engineering situations. This motivates students to learn new concepts and gives them a taste of practical engineering experience. Use of the Computer - Computer usage is closely integrated into the text and homework exercises.



Introductory Statistics 2e

Author : Barbara Illowsky

Publisher :

Page : 2106 pages

File Size : 10,37 MB

Release : 2023-12-13

Category : Mathematics

ISBN :

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Book Description

Introductory Statistics 2e provides an engaging, practical, and thorough overview of the core concepts and skills taught in most one-semester statistics courses. The text focuses on diverse applications from a variety of fields and societal contexts, including business, healthcare, sciences, sociology, political science, computing, and several others. The material supports students with conceptual narratives, detailed step-by-step examples, and a wealth of illustrations, as well as collaborative exercises, technology integration problems, and statistics labs. The text assumes some knowledge of intermediate algebra, and includes thousands of problems and exercises that offer instructors and students ample opportunity to explore and reinforce useful statistical skills. This is an adaptation of Introductory Statistics 2e by OpenStax. You can access the textbook as pdf for free at openstax.org. Minor editorial changes were made to ensure a better ebook reading experience. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution 4.0 International License.



Introduction to Engineering Statistics and Lean Sigma

Author : Theodore T. Allen

Publisher : Springer Science & Business Media

Page : 573 pages

File Size : 47,38 MB

Release : 2010-04-23

Category : Technology & Engineering

ISBN : 1849960003

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Book Description

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.



Statistical Methods for Quality Assurance

Author : Stephen B. Vardeman

Publisher : Springer

Page : 447 pages

File Size : 13,68 MB

Release : 2016-08-26

Category : Mathematics

ISBN : 038779106X

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Book Description

This undergraduate statistical quality assurance textbook clearly shows with real projects, cases and data sets how statistical quality control tools are used in practice. Among the topics covered is a practical evaluation of measurement effectiveness for both continuous and discrete data. Gauge Reproducibility and Repeatability methodology (including confidence intervals for Repeatability, Reproducibility and the Gauge Capability Ratio) is thoroughly developed. Process capability indices and corresponding confidence intervals are also explained. In addition to process monitoring techniques, experimental design and analysis for process improvement are carefully presented. Factorial and Fractional Factorial arrangements of treatments and Response Surface methods are covered. Integrated throughout the book are rich sets of examples and problems that help readers gain a better understanding of where and how to apply statistical quality control tools. These large and realistic problem sets in combination with the streamlined approach of the text and extensive supporting material facilitate reader understanding. Second Edition Improvements Extensive coverage of measurement quality evaluation (in addition to ANOVA Gauge R&R methodologies) New end-of-section exercises and revised-end-of-chapter exercises Two full sets of slides, one with audio to assist student preparation outside-of-class and another appropriate for professors’ lectures Substantial supporting material Supporting Material Seven R programs that support variables and attributes control chart construction and analyses, Gauge R&R methods, analyses of Fractional Factorial studies, Propagation of Error analyses and Response Surface analyses Documentation for the R programs Excel data files associated with the end-of-chapter problem sets, most from real engineering settings



Statistical Reasoning in the Behavioral Sciences

Author : Bruce M. King

Publisher : John Wiley & Sons

Page : 976 pages

File Size : 27,67 MB

Release : 2018-04-24

Category : Psychology

ISBN : 1119379733

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Book Description

Cited by more than 300 scholars, Statistical Reasoning in the Behavioral Sciences continues to provide streamlined resources and easy-to-understand information on statistics in the behavioral sciences and related fields, including psychology, education, human resources management, and sociology. Students and professionals in the behavioral sciences will develop an understanding of statistical logic and procedures, the properties of statistical devices, and the importance of the assumptions underlying statistical tools. This revised and updated edition continues to follow the recommendations of the APA Task Force on Statistical Inference and greatly expands the information on testing hypotheses about single means. The Seventh Edition moves from a focus on the use of computers in statistics to a more precise look at statistical software. The “Point of Controversy” feature embedded throughout the text provides current discussions of exciting and hotly debated topics in the field. Readers will appreciate how the comprehensive graphs, tables, cartoons and photographs lend vibrancy to all of the material covered in the text.