Description
Book SynopsisThis 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.
Table of ContentsIntroduction of Quality Engineering; Analysis of Quality Information and Quality Improvement Team Effort; Fundamentals of Designing Experiments; Orthogonal Array Experiments; Parameter Design for Continuous Data; Parameter Design for Discrete Data; Parameter Design for Dynamic Characteristics; Alternative Parameter Design and Other Considerations; Tolerance Design; Robust Response Surface Design and Analysis; Six Sigma for Management Innovation; Data Technology in Knowledge-Based Society; Design for Six Sigma in Six Sigma Implementation; DFSS Methodology and Robust Designs; Case Studies of Robust Design in Six Sigma and DFSS.
