This book gives the reader tools for optimizing performance and reducing variation in manufacturing. Statistical process control and Taguchi methods are featured in the book along with other less published techniques. The book covers the product life cycle from design to manufacturing and is aimed at improving industrial practice. Methods are shown through case studies and extensive graphics are used to illustrate points.

Optimization in Quality Control presents a broad survey of the state of the art in optimization in quality, and focuses on industrial and national competitiveness. Each chapter has been carefully developed and refereed anonymously by experts in the area of optimization in quality control. Some of the topics covered in this volume include: fundamentals of optimization techniques contemporary approaches to optimization models in process control economic design of control charts determining optimal target values in multiple criteria economic selection models examining quality improvement schemes by trading off between expected warranty servicing costs and increasing manufacturing costs designing optimal inspection plans. This book will serve as an important reference source for academics, professionals and researchers.

In a world where innovation and sustainability are paramount, Fundamentals of Design of Experiments for Automotive Engineering: Volume I serves as a definitive guide to harnessing the power of statistical thinking in product development. As first of four volumes in SAE International’s DOE for Product Reliability Growth series, this book presents a practical, application-focused approach by emphasizing DOE as a dynamic tool for automotive engineers. It showcases real-world examples, demonstrating how process improvements and system optimizations can significantly enhance product reliability. The author, Yung Chiang, leverages extensive product development expertise to present a comprehensive process that ensures product performance and reliability throughout its entire lifecycle. Whether individuals are involved in research, design, testing, manufacturing, or marketing, this essential reference equips them with the skills needed to excel in their respective roles. This book explores the potential of Reliability and Sustainability with DOE, featuring the following topics: - Fundamental prerequisites for deploying DOE: Product reliability processes, measurement uncertainty, failure analysis, and design for reliability. - Full factorial design 2K: A system identification tool for relating objectives to factors and understanding main and interactive effects. - Fractional factorial design 2RK-P: Ideal for identifying main effects and 2-factor interactions. - General fractional factorial design LK-P: Systematically identification of significant inputs and analysis of nonlinear behaviors. - Composite designs as response surface methods: Resolving interactions and optimizing decisions with limited factors. - Adapting to practical challenges with “short” DOE: Leveraging optimization schemes like D-optimality, and A-optimality for optimal results. Readers are encouraged not to allow product failures to hinder progress but to embrace the "statistical thinking" embedded in DOE. This book can illuminate the path to designing products that stand the test of time, resulting in satisfied customers and thriving businesses. (ISBN 9781468606027, ISBN 9781468606034, ISBN 9781468606041, DOI 10.4271/9781468606034)

The Six Sigma concept has enjoyed triumphant success throughout the business world for two decades, contributing to significant net income improvement for many companies. This successful concept has been supplemented with the tools of Lean Management, a set of strategies for improving product quality and delivery performance and reducing cost. Six Sigma+Lean links the tried-and-tested tools of both programs in the proven DMAIC process model. The chronology matches that of the approach taken in a Six Sigma+Lean improvement project.

In this volume of the Six Sigma and Beyond series, quality engineering expert D.H. Stamatis focuses on how Statistical Process Control (SPC) relates to Six Sigma. He emphasizes the "why we do" and "how to do" SPC in many different environments. The book provides readers with an overview of SPC in easy-to-follow, easy-to-understand terms. The author reviews and explains traditional SPC tools and how they relate to Six Sigma and goes on to cover the use of advanced techniques. In addition, he addresses issues that concern service SPC and short run processes, explores the issue of capability for both the short run and the long run, and discusses topics in measurement.

Variability arises in multistage manufacturing processes (MMPs) from a variety of sources. Variation reduction demands data fusion from product/process design, manufacturing process data, and quality measurement. Statistical process control (SPC), with a focus on quality data alone, only tells half of the story and is a passive method, taking corre

This volume presents recent research in reliability and quality theory and its applications by many leading experts in the field. The subjects covered include reliability optimization, software reliability, maintenance, quality engineering, system reliability, Monte Carlo simulation, tolerance design optimization, manufacturing system estimation, neural networks, software quality assessment, optimization design of life tests, software quality, reliability-centered maintenance, multivariate control chart, methodology for measurement of test effectiveness, imperfect preventive maintenance, Markovian reliability modeling, accelerated life testing, and system availability assessment. The book will serve as a reference for postgraduate students and will also prove useful for practitioners and researchers in reliability and quality engineering.

In the world of modern engineering, rigorous and definite design methodologies are needed. However, many parts of engineering design are performed in either an ad-hoc manner or based on the intuition of the engineer. This is the first book to look at both stages of the design process – conceptual design and detailed design – and detail design methodologies for every step of the design process. Case studies show how practical design problems can be solved with analytic design methods. This book is an excellent introduction to the subject. The book’s practical focus will make the book useful to practicing engineers as a practical handbook of design.

Failure modes and effects analysis (FMEA); Reliability; Product Development; Design Process; Test Procedures "Explore Product Design and Testing for Automotive Engineering: Volume II, an essential guide reshaping vehicle manufacturing with unprecedented reliability. As part of SAE International’s DOE for Product Reliability Growth series, this practical resource introduces cutting-edge methodologies crucial for predicting and improving product reliability in an era of automotive electrification. The book navigates statistical tolerance design, showcasing how variability in part fabrication and assembly can enhance reliability and sustainability. Key topics include: - Statistical tolerance design's impact on manufacturing and material selection, focusing on non-normal distributions' effects on product assembly and cost. Methods like maximum likelihood estimators and Monte Carlo simulations are used for assembly strategy synthesis. - Reliability DOEs using log-location-scale distributions to estimate lifetimes of non-normally distributed components, especially in accelerated life testing. It covers transformations optimizing parts and system designs under the lognormal distribution. - Weibull distribution (DOE-W) for characterizing lifetimes affected by various failure modes, detailing parameter assessment methods and real-world applications. The book also introduces reliability design of experiments based on the exponential distribution (DOE-E). - Importance of predicting lifecycles and enhancing reliability through qualitative and stepwise accelerated life tests. Integration of physics of failure with statistical methods like Weibull statistics and lognormal approximation enhances analysis credibility. - Inferential mechanisms such as the Arrhenius and Eyring models in predicting automotive component lifecycles, refining product life prediction based on reliability DOEs. Whether you're an engineer, researcher, or automotive professional, this book equips you to navigate reliability engineering confidently. Revolutionize your approach to product design and testing with Product Design and Testing for Automotive Engineering, your definitive companion in shaping the future of automotive reliability." (ISBN 9781468607703 ISBN 9781468607697 ISBN 9781468607727 DOI 10.4271/9781468607697)