Robust Design

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.

The book presents a systematic and efficient method to design high quality / reliability and high performance products / processes at low cost. Contains case studies from diverse engineering fields to describe Robust Design / Taguchi method.Some topics covered are: orthogonal arrays, Signal-to-Noise ratios as design quality metric, computer-aided robust design techniques, and more.

In the past few years, the concept of robustness has been the subject of growing interest in the natural and engineering sciences. Building on traditional fields such as stability, reliability, and control theory, the study of robustness focuses on the ability of a system to maintain specified features when subject to assemblages of perturbations either internal or external. In most cases, the system of interest is not in equilibrium, and the perturbations are typically such that it is unrealistic to attempt estimations of their supports and distributions.

Based on deep theoretical as well as practical experience in Reliability and Quality Sciences, Robust Design Methodology for Reliability constructively addresses practical reliability problems. It offers a comprehensive design theory for reliability, utilizing robust design methodology and six sigma frameworks. In particular, the relation between un-reliability and variation and uncertainty is explored and reliability improvement measures in early product development stages are suggested. Many companies today utilise design for Six Sigma (DfSS) for strategic improvement of the design process, but often without explicitly describing the reliability perspective; this book explains how reliability design can relate to and work with DfSS and illustrates this with real–world problems. The contributors advocate designing for robustness, i.e. insensitivity to variation in the early stages of product design development. Methods for rational treatment of uncertainties in model assumptions are also presented. This book promotes a new approach to reliability thinking that addresses the design process and proneness to failure in the design phase via sensitivity to variation and uncertainty; includes contributions from both academics and industry practitioners with a broad scope of expertise, including quality science, mathematical statistics and reliability engineering; takes the innovative approach of promoting the study of variation and uncertainty as a basis for reliability work; includes case studies and illustrative examples that translate the theory into practice. Robust Design Methodology for Reliability provides a starting point for new thinking in practical reliability improvement work that will appeal to advanced designers and reliability specialists in academia and industry including fatigue engineers, product development and process/ quality professionals, especially those interested in and/ or using the DfSS framework.

In 1980, I received a grant from Aoyama-gakuin university to come to the United States to assist American Industry improve the quality of their products. In a small way this was to repay the help the US had given Japan after the war. In the summer of 1980, I visited the AT&T Bell Laboratories Quality Assurance Center, the organization that founded modern quality control. The result of my first summer at AT&T was an experiment with an orthogonal array design of size 18 (OA18) for optimization of an LSI fabrication process. As a measure of quality, the quantity "signal-ta-noise" ratio was to be optimized. Since then, this experi mental approach has been named "robust design" and has attracted the attention of both engineers and statisticians. My colleagues at Bell Laboratories have written several expository articles and a few theoretical papers on robust design from the viewpoint of statistics. Because so many people have asked for copies of these papers, it has been decided to publish them in a book form. This anthology is the result of these efforts. Despite the fact that quality engineering borrows some technical words from traditional design of experiments, the goals of quality engineering are different from those of statistics. For example, suppose there are two vendors. One vendor supplies products whose quality characteristic has a normal distribution with the mean on target (the desired value) and a certain standard deviation.

Robust Design of Microelectronics Assemblies Against Mechanical Shock, Temperature and Moisture discusses how the reliability of packaging components is a prime concern to electronics manufacturers. The text presents a thorough review of this important field of research, providing users with a practical guide that discusses theoretical aspects, experimental results, and modeling techniques. The authors use their extensive experience to produce detailed chapters covering temperature, moisture, and mechanical shock induced failure, adhesive interconnects, and viscoelasticity. Useful program files and macros are also included. Discusses how the reliability of packaging components is a prime concern to electronics manufacturers Presents a thorough review of this important field of research, providing users with a practical guide that discusses theoretical aspects, experimental results, and modeling techniques Includes program files and macros for additional study

This book is written primarily for engineers who want to use statistical designs for quality engineering, and for statisticians who want to know the wide range of applications of experimental design in the manufacturing industry. Significantly, Robust Design and Analysis for Quality Engineering addresses the following techniques: Taguchi's quality engineering approaches, concepts of robustness in experimental designs, response surface design and its applications, Pareto-type ANOVA for analysis of parameter design, and strategies of quality improvement efforts through robust design and analysis. Through a series of real case studies, these important techniques are made readily accessible to all readers. This is also the key text for senior undergraduate and postgraduate students studying engineering and experimental design.

Explains how to prevent quality problems in the early stages of product development and design, how to use the dynamic signal-to- noise ratio as the performance index for robustness of product functions, and how to evaluate methods of data collection. The book focuses on dynamic characteristics, foll.