Quality Engineering

Off-Line Methods and Applications
1. Auflage 2013
ISBN: 978-1-4665-6947-8
Verlag: Taylor & Francis Inc

Buch, Englisch, 394 Seiten, Format (B × H): 181 mm x 261 mm, Gewicht: 940 g

As quality becomes an increasingly essential factor for achieving business success, building quality improvement into all stages—product planning, product design, and process design—instead of just manufacturing has also become essential. Quality Engineering: Off-Line Methods and Applications explores how to use quality engineering methods and other modern techniques to ensure design optimization at every stage. The book takes a broad approach, focusing on the user’s perspective and building a well-structured framework for the study and implementation of quality engineering.

Starting with the basics, this book presents an overall picture of quality engineering. The author delineates quality engineering methods such as DOE, Taguchi, and RSM as well as computational intelligence approaches. He discusses how to use a general computational intelligence approach to improve product quality and process performance. He also provides extensive examples and case studies, numerous exercises, and a glossary of basic terms.

By adopting quality engineering, the defect rate during manufacturing shows noticeable improvement, the production cost is significantly lower, and the quality and reliability of products can be enhanced. Taking an integrated approach that makes the methods of upstream quality improvement accessible, without extensive mathematical treatments, this book is both a practical reference and an excellent textbook.

Zielgruppe

Graduate students studying quality engineering within manufacturing and mechanical engineering; graduate engineers taking part in CPD quality engineering design courses; academics and lecturers teaching quality engineering.

Autoren/Hrsg.

Su, Chao-Ton

Fachgebiete

• Technische Wissenschaften Maschinenbau | Werkstoffkunde Produktionstechnik Industrielle Qualitätskontrolle

Inhaltsverzeichnis

Introduction. Fundamentals of Experimental Design. Principles of Quality Engineering. Utilization of Orthogonal Arrays. Quality Loss Function and Static Signal-to-Noise Ratios. Parameter Design for Static Characteristics. Parameter Design for Dynamic Characteristics. Implementing Parameter Design. Tolerance Design. Mahalanobis-Taguchi System. Response Surface Methodology. Parameter Design Using Computational Intelligence. Appendix. References. Glossary. Index.

Über Autor(innen)

Chao-Ton Su is a chair professor with the Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu, Taiwan.