Quality Improvement, 9th edition

Quality Control focuses on the quantitative aspects of quality improvement, with sufficient theory to help you develop a solid understanding of basic quality principles. The text presents probability and statistical techniques using simpler math or developed via tables and charts, making the information easier to digest.

For undergraduate and graduate-level courses in Quality Control, Statistical Process Control, Quality Improvement, and Quality Assurance. This book will be valuable in programs such as Quality Improvement, Lean Six Sigma, Quality Control, and Statistical Process Control; in Associate Degree in Quality and other technical programs; in Baccalaureate programs in Engineering, Technology, Health Care, Education, and Business; and in Masters Degree programs in business.

Formerly titled Quality Control, the field’s most accessible introduction to quality has been renamed and revamped to focus on quantitative aspects of quality improvement. New chapters on Lean Enterprise, Six Sigma, Experimental Design, and Taguchi’s Quality Engineering have been added, and this new Ninth Edition adds comprehensive coverage of fundamental statistical quality improvement concepts. A practical state-of-the-art approach is stressed throughout, and sufficient theory is presented to ensure that students develop a solid understanding of basic quality principles. To improve accessibility, probability and statistical techniques are presented through simpler math or developed via tables and charts. As with previous editions, this text is written to serve a widely diverse audience of students, including the growing number of “math shy” individuals who must play key roles in quality improvement.

Fully prepares students to participate in modern Total Quality Management programs and initiatives. Offers a full chapter introducing TQM principles and Practices, and another on TQM tools and techniques, establishing a foundation for deeper coverage of specific quality tools, techniques, and standards later in the text.

Gives students hands-on practice with realistic quality data. Contains exercises at the end of each chapter; boxed example problems throughout; and a CD-ROM of quality data files using the Microsoft Excel format.

Gives students the conceptual and qualitative understanding they need before they can master quantitative techniques. Prepares students for quantitative quality analysis by first introducing qualitative aspects of SPC, fundamentals of statistics, control charts for variables and attributes, and other crucial concepts and techniques.  

Introduces students to the field’s most important standards and awards. Includes summaries of the ISO 14000 and FMEA standards, as well as information on the categories and criteria for winning the Malcolm Baldrige National Quality Award.

Helps students understand exactly what they will be learning. Provides clear learning objectives at the beginning of each chapter, to help students focus their study.

Helps students see how and why the quality improvement discipline emerged, and how it has evolved. Includes historical review and introductory sections placing key concepts and techniques in context.

This edition has been thoroughly reworked to focus on the quantitative aspects of quality improvement, while retaining the accessibility and user-friendliness that has made it a market leader through eight previous editions.

• Prepares students to participate in any aspect of quality improvement — quantitative, qualitative, or both 

New! New introductory chapter–briefly describing all leading quality improvement tools and techniques

• Gives students a quick jumpstart for understanding the broad discipline of quality improvement 

• Introduces students to powerful new techniques for continuously improving value across the entire value stream, and beyond the borders of the individual corporation 

• Enables students to work successfully in any role or organization that participates in Six Sigma

New! Thorough introduction to experimental design–including hypotheses, t and F tests, one-factor, orthogonal design, point and interval estimates, two factors, full factorials, and fractional factorials     

• Introduces students to the crucial issues associated with experimental design, helping them recognize and avoid problems that might compromise quality control or improvement

New! Chapter-length introduction to Taguchi’s Quality Engineering–including objectives, loss function, orthogonal arrays, S/N ratios, and parameter and tolerance design

• Helps students apply Taguchi’s pioneering methods in areas ranging from manufacturing and engineering to healthcare and marketing