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.

The success of any product sold to consumers is based, largely, on the longevity of the product. This concept can be extended by various methods of improvement including optimizing the initial creation structures which can lead to a more desired product and extend the product's time on the market. Design and Optimization of Mechanical Engineering Products is an essential research source that explores the structure and processes used in creating goods and the methods by which these goods are improved in order to continue competitiveness in the consumer market. Featuring coverage on a broad range of topics including modeling and simulation, new product development, and multi-criteria decision making, this publication is targeted toward students, practitioners, researchers, engineers, and academicians.

This book is written primarily for engineers and researchers who use statistical robust design for quality engineering and Six Sigma, and for statisticians who wish to know about the wide range of applications of experimental design in industry. It is a valuable guide and reference material for students, managers, quality improvement specialists and other professionals interested in Taguchi's robust design methods as well as the implementation of Six Sigma. This book can also be useful to those who would like to learn about the role of Robust Design within the Six Sigma (Improve phase) methodology and Design for Six Sigma (DFSS) (Optimize) methodology. It combines classical experimental design methods with those of Taguchi's robust designs, demonstrating their prowess in DFSS and suggesting new directions for the development of statistical design and analysis.

This work presents the concepts of process design, problem identification, problem-solving and process optimization. It provides the basic tools needed to increase the consistency and profitability of manufacturing options, stressing the paradigms of improvement and emphasizing the hands-on use of tools furnished. The book introduces basic experimental design principles and avoids complicated statistical formulae.

Robust Design is the procedure used by design engineers to reduce the effects of order to produce the highest quality products possible. This book includes real life case studies focusing on mechanical, chemical and imaging design that illustrate potential problems and their solutions and offers WinRobust Lite software and practice problems.