Elementary Statistical Quality Control 2nd Edition
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| Author | : John T. Burr |
| Publisher | : CRC Press |
| Total Pages | : 467 |
| Release | : 2004-12-28 |
| Genre | : Business & Economics |
| ISBN | : 0824790529 |
Maintaining the reader-friendly features of its popular predecessor, the Second Edition illustrates fundamental principles and practices in statistical quality control for improved quality, reliability, and productivity in the management of production processes and industrial and business operations. Presenting key concepts of statistical quality control in a simple and straightforward manner, this reference will provide a solid foundation in statistical quality control theory, background, and applications. Moving from elementary topics to sampling by variables, sound tolerancing, and relationships between variables, this reference
| Author | : Irving Wingate Burr |
| Publisher | : CRC Press |
| Total Pages | : 0 |
| Release | : 1979-01-01 |
| Genre | : Business & Economics |
| ISBN | : 9780824766863 |
| Author | : Bhisham C. Gupta |
| Publisher | : John Wiley & Sons |
| Total Pages | : 400 |
| Release | : 2021-07-23 |
| Genre | : Technology & Engineering |
| ISBN | : 1119671728 |
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.
| Author | : Douglas C. Montgomery |
| Publisher | : John Wiley & Sons |
| Total Pages | : 768 |
| Release | : 2020-06-23 |
| Genre | : Technology & Engineering |
| ISBN | : 1119723094 |
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, and incorporation of Minitab statistics software, provides students with a solid base of conceptual and practical knowledge.
| Author | : Eugene Lodewick Grant |
| Publisher | : McGraw-Hill Companies |
| Total Pages | : 710 |
| Release | : 1980 |
| Genre | : Business & Economics |
| ISBN | : |
This title is a substantial revision of one of the leading textbooks designed for the statistical quality control course taught in departments of industrial engineering, operations research and statistics . While maintaining its already successful writing style and pedagogy, this title has also incorporated key organizational changes in order to reflect recent trends in the field. The text features large quantity of examples and student problems and a strong introduction to the proper use and misuse of control charts. In this edition several chapters were streamlined, and consolidations and profitability were brought forward in the text. There is new material on experimental design, a reduced emphasis on acceptance sampling, and enhanced attention to the managerial and organizational aspects of quality control. Free SPC expert software is packaged with the text for use as a statistical and graphical tool. Text plus 3.5" diskette. Copyright © Libri GmbH. All rights reserved.
| Author | : K. KRISHNAIAH |
| Publisher | : PHI Learning Pvt. Ltd. |
| Total Pages | : 499 |
| Release | : 2014-05-12 |
| Genre | : Technology & Engineering |
| ISBN | : 812034975X |
Primarily intended for the undergraduate students of industrial, production, mechanical and manufacturing engineering, and postgraduate students of industrial, quality engineering and management and industrial engineering and management, this book fills the gap between theory and practice of tools and techniques of quality control and quality improvement. In this book, the principles and concepts are presented clearly and logically with necessary numerical illustrations to reinforce the understanding of the subject matter. The book is organized in two parts. Part I deals with statistical quality control. It starts with the fundamentals of statistics and quality followed by elaborate discussion on statistical process control, process and gauge capability studies with emphasis on their practical application. It also covers detailed discussion on the various types of control charts used to monitor and control quality of processes and products. It includes acceptance sampling inspection procedures and standard sampling systems. Part II deals with quality improvement techniques/methods. It is a data driven approach that discusses the application of Design of Experiments and Taguchi Methods for improving quality of processes and products. A comprehensive discussion on total quality management is also presented. KEY FEATURES • Provides a well structured procedure for the application of all the tools and techniques. • Includes Shainin DOE tools widely used in Six sigma projects. • Demonstrates the application of quality improvement techniques through real life case studies.
| Author | : George E. P. Box |
| Publisher | : John Wiley & Sons |
| Total Pages | : 360 |
| Release | : 2011-09-09 |
| Genre | : Mathematics |
| ISBN | : 1118164466 |
Praise for the First Edition "This book . . . is a significant addition to the literature onstatistical practice . . . should be of considerable interest tothose interested in these topics."—International Journal ofForecasting Recent research has shown that monitoring techniques alone areinadequate for modern Statistical Process Control (SPC), and thereexists a need for these techniques to be augmented by methods thatindicate when occasional process adjustment is necessary.Statistical Control by Monitoring and Adjustment, Second Editionpresents the relationship among these concepts and elementary ideasfrom Engineering Process Control (EPC), demonstrating how thepowerful synergistic association between SPC and EPC can solvenumerous problems that are frequently encountered in processmonitoring and adjustment. The book begins with a discussion of SPC as it was originallyconceived by Dr. Walter A. Shewhart and Dr. W. Edwards Deming.Subsequent chapters outline the basics of the new integration ofSPC and EPC, which is not available in other related books.Thorough coverage of time series analysis for forecasting, processdynamics, and non-stationary models is also provided, and thesesections have been carefully written so as to require only anelementary understanding of mathematics. Extensive graphicalexplanations and computational tables accompany the numerousexamples that are provided throughout each chapter, and a helpfulselection of problems and solutions further facilitatesunderstanding. Statistical Control by Monitoring and Adjustment, Second Editionis an excellent book for courses on applied statistics andindustrial engineering at the upper-undergraduate and graduatelevels. It also serves as a valuable reference for statisticiansand quality control practitioners working in industry.
| Author | : Irving W. Burr |
| Publisher | : Routledge |
| Total Pages | : 540 |
| Release | : 2018-05-04 |
| Genre | : Business & Economics |
| ISBN | : 1351414194 |
This book focuses on statistical methods useful in quality control, emphasizing on data-analysis and decision-making. These techniques are also of great use in areas such as laboratory analyses and research. The problems and examples presented are from actual cases encountered in the industry.
| Author | : Sven Knoth |
| Publisher | : Springer Nature |
| Total Pages | : 410 |
| Release | : 2021-05-15 |
| Genre | : Mathematics |
| ISBN | : 3030678563 |
This contributed book focuses on major aspects of statistical quality control, shares insights into important new developments in the field, and adapts established statistical quality control methods for use in e.g. big data, network analysis and medical applications. The content is divided into two parts, the first of which mainly addresses statistical process control, also known as statistical process monitoring. In turn, the second part explores selected topics in statistical quality control, including measurement uncertainty analysis and data quality. The peer-reviewed contributions gathered here were originally presented at the 13th International Workshop on Intelligent Statistical Quality Control, ISQC 2019, held in Hong Kong on August 12-14, 2019. Taken together, they bridge the gap between theory and practice, making the book of interest to both practitioners and researchers in the field of statistical quality control.
| Author | : Richard E. DeVor |
| Publisher | : Pearson |
| Total Pages | : 968 |
| Release | : 2007 |
| Genre | : Business & Economics |
| ISBN | : |
Emphasizing proper methods for data collection, control chart construction and interpretation, and fault diagnosis for process improvement, this text blends statistical process control (SPC) and design of experiments (DOE) concepts and methods for quality design and improvement. Importance is placed on both the philosophical/conceptual underpinnings and the techniques and methods of SPC and DOE. The concepts and methods of Taguchi for quality design are combined with more traditional experimental design methods to promote the importance of viewing quality from an engineering design perspective.
