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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
State-of-the-Art Coverage of the Most Widely Used Acceptance Sampling Techniques Cohesively Incorporates Theory and Practice Reflecting the recent resurgence of interest in this field, Acceptance Sampling in Quality Control, Second Edition presents the state of the art in the methodology of sampling and explores its advantages and limitations. The book also looks at how acceptance control can support applications of statistical process control and help in the evaluation of products. New to the Second Edition Coverage of ISO 2859 and 3951 standards and the ASTM version (E2234) of MIL-STD-105E A new section on credit-based sampling plans Greater emphasis on sampling schemes with switching rules More extensive discussion of accept zero plans, including tightened-normal-tightened (TNT), credit-based, the Nelson monograph for c=0, and MIL-STD-1916 Providing valuable guidelines for choosing appropriate procedures, this comprehensive second edition encompasses the most widely used acceptance sampling techniques. It lucidly provides a broad theoretical understanding of the field while offering all the information needed for the practical application of acceptance sampling plans in industry.
"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."--
The new edition of the best-selling reference on statistical quality control has been updated to include definitions re-written for a wider audience to grasp the meaning of technical terms. These definitions also parallel national and international standards and are categorized into sections that make it easy to identify by subject matter.Terms have been extensively cross-referenced and alphabetized in one handy reference along with a comprehensive collection of statistical tables that make it easy to access all of the information needed for statistical calculation. New items added to this edition include a guide for control chart selection and g and h control charts. Basic statistical measures and equation examples make this an outstanding resource for every quality professional as well as a great resource for preparing for the Certified Quality Engineer, Certified Mechanical Inspector, and Certified Quality Technician's exams.
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.
This book is written for the Six Sigma Black Belt who needs an understanding of many statistical methods but does not use all of these methods every day. It is intended to be used as a quick reference, providing basic details, step-by-step instructions, and Minitab statistical software instructions. Six Sigma Black Belts typically use a statistical program such as Minitab to perform calculations, but an understanding of the underlying statistics is still needed. Anybody can type data into a program; a Black Belt must be capable of understanding which hypothesis test is appropriate for a given use, as well as the assumptions that must be met to correctly perform the hypothesis test. The methods presented here are laid out according to the Six Sigma DMAIC (Define, Measure, Analyze, Improve, Control) phases in which they are typically used. However, these methods can also be applied outside of a Six Sigma project, such as when one simply needs to determine whether there is a difference in the means of two processes producing the same parts. A Six Sigma Black Belt using Statistics for Six Sigma Black Belts will be able to quickly zero in on appropriate methods and follow the examples to reach the correct statistical conclusions.
Acceptance Sampling in Quality Control, Third Edition presents the state of the art in the methodology of sampling while integrating both theory and best practices. It discusses various standards, including those from the ISO, MIL-STD and ASTM and explores how to set quality levels. The book also includes problems at the end of each chapter with solutions. This edition improves upon the previous editions especially in the areas of software applications and compliance sampling plans. New to the Third Edition: Numerous Microsoft Excel templates to address sampling plans are used. Commercial software applications are discussed at the end of many chapters. Discussion of quick switching systems has been expanded to account for the considerable recent activity in this area. Added discussion of zero acceptance number chained quick switching systems.
This book is a desk reference and instructional aid for those individuals currently involved with, or preparing for involvement with, Six Sigma project teams. As Six Sigma team members, Green Belts help select, collect data for, and assist with the interpretation of a variety of statistical or quantitative tools within the context of the Six Sigma methodology. The second in a four-book series geared specifically for these Green Belt activities, this book provides a thorough discussion of statistical quality control (SQC) tools. These tools are introduced and discussed from the perspective of application rather than theoretical development. From this perspective, readers are taught to consider the SQC tools as statistical “alarm bells” that send signals when there are one or more problems with a particular process. Guidance is also given on the use of Minitab and JMP in doing these various SQC applications. In addition, examples and sample problems from all industries appear throughout the book to aid a Green Belt's comprehension of the material.
"Considerations of Quality play a prominent role in all fields -- particularly with recently focused attention on issues of consumerism, product and professional liability, and government regulation. American industries must improve quality if they are to remain competitive in world markets. "
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