The quality knowledge landscape is rapidly evolving alongside advancements in information technology and manufacturing methods. As data science transforms information processing, quality decisions are becoming more data-driven, while innovations like additive manufacturing and Industry 4.0 automation demand new measurement and control approaches. This convergence necessitates updated educational resources to equip future engineers and managers with the integrated expertise needed for implementing modern quality systems that span entire production ecosystems rather than operating in departmental silos.A leader in its field, A First Course in Quality Engineering: Integrating Statistical and Management Methods of Quality, Fourth Edition is completely updated and continues to offer a balanced treatment of both statistical and management methods of quality and at the same time gives the theoretical background of the statistical methods. This textbook presents many examples and exercises taken from real-world processes and includes mini-projects from the authors' consulting work that shows how the tools are employed in solving some difficult real-world problems. It addresses major systems for quality management such as ISO 9000 and Baldrige Criteria which are explained in plain, non-legal language and provides updated material on new quality methods developed to meet the evolving changes in the digital world such as data analytics in Industry 4.0.This textbook is a key source for quality technology that is completely updated and includes a new chapter titled "e;Quality for the 21st Century."e; For an instructor, this premium textbook is a ready source of reference updated by experts in the field. For the student, it contains the latest material along with long-established tools. Lastly for the professional, this book remains a great training tool for corporate trainers.A Solutions Manual and PowerPoint slides are available for qualified textbook adoptions.

The quality knowledge landscape is rapidly evolving alongside advancements in information technology and manufacturing methods. As data science transforms information processing, quality decisions are becoming more data-driven, while innovations like additive manufacturing and Industry 4.0 automation demand new measurement and control approaches. This convergence necessitates updated educational resources to equip future engineers and managers with the integrated expertise needed for implementing modern quality systems that span entire production ecosystems rather than operating in departmental silos.A leader in its field, A First Course in Quality Engineering: Integrating Statistical and Management Methods of Quality, Fourth Edition is completely updated and continues to offer a balanced treatment of both statistical and management methods of quality and at the same time gives the theoretical background of the statistical methods. This textbook presents many examples and exercises taken from real-world processes and includes mini-projects from the authors' consulting work that shows how the tools are employed in solving some difficult real-world problems. It addresses major systems for quality management such as ISO 9000 and Baldrige Criteria which are explained in plain, non-legal language and provides updated material on new quality methods developed to meet the evolving changes in the digital world such as data analytics in Industry 4.0.This textbook is a key source for quality technology that is completely updated and includes a new chapter titled "e;Quality for the 21st Century."e; For an instructor, this premium textbook is a ready source of reference updated by experts in the field. For the student, it contains the latest material along with long-established tools. Lastly for the professional, this book remains a great training tool for corporate trainers.A Solutions Manual and PowerPoint slides are available for qualified textbook adoptions.

The quality knowledge landscape is rapidly evolving alongside advancements in information technology and manufacturing methods. As data science transforms information processing, quality decisions are becoming more data-driven, while innovations like additive manufacturing and Industry 4.0 automation demand new measurement and control approaches. This convergence necessitates updated educational resources to equip future engineers and managers with the integrated expertise needed for implementing modern quality systems that span entire production ecosystems rather than operating in departmental silos.A leader in its field, A First Course in Quality Engineering: Integrating Statistical and Management Methods of Quality, Fourth Edition is completely updated and continues to offer a balanced treatment of both statistical and management methods of quality and at the same time gives the theoretical background of the statistical methods. This textbook presents many examples and exercises taken from real-world processes and includes mini-projects from the authors' consulting work that shows how the tools are employed in solving some difficult real-world problems. It addresses major systems for quality management such as ISO 9000 and Baldrige Criteria which are explained in plain, non-legal language and provides updated material on new quality methods developed to meet the evolving changes in the digital world such as data analytics in Industry 4.0.This textbook is a key source for quality technology that is completely updated and includes a new chapter titled "e;Quality for the 21st Century."e; For an instructor, this premium textbook is a ready source of reference updated by experts in the field. For the student, it contains the latest material along with long-established tools. Lastly for the professional, this book remains a great training tool for corporate trainers.A Solutions Manual and PowerPoint slides are available for qualified textbook adoptions.