Fundamentals Of Design Of Experiments For Automotive Engineering
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Fundamentals of Design of Experiments for Automotive Engineering Volume I
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)
Fundamentals of Design of Experiments for Automotive Engineering
Front Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Acronyms -- Nomenclature -- Introduction -- Chapter 1: Reliability Deployment -- 1.1 Product Reliability Realization -- 1.1.1 Product Quality, Robustness, and Reliability -- 1.1.2 Realization Process of Product Reliability -- 1.1.3 Tools for Reliability Realization -- 1.1.4 Advanced Reliability Planning -- 1.1.5 Reliability Lauded in VOC -- 1.1.6 Product Reliability Growth -- 1.2 Uncertainty of Measurement -- 1.2.1 Accuracy: Precision and Trueness -- 1.2.2 Essential Elements of Measurement -- 1.3 Unreliability -- 1.3.1 Physical and Functional Failures -- 1.3.2 Probability of Product Failure -- 1.3.3 Failure Measured by Time -- 1.4 Design for Reliability -- 1.4.1 Reference Model and Simulation for System Identification -- 1.4.2 Boundary Diagram -- 1.4.3 Parameter Diagram (P-Diagram) -- 1.4.4 Fishbone Diagram -- 1.4.5 Variation Modes and Effect Analysis -- 1.5 Classification of DOE -- 1.5.1 Basic Types of DOE -- 1.5.2 Acceptance Sampling and Test Plans -- 1.5.3 Statistical Tolerance Design -- 1.5.4 Manufacturing Reliability -- 1.5.5 Supply Chain Reliability -- 1.5.6 Operational Reliability -- 1.5.7 Marketing Reliability -- 1.5.8 Holistic Approach -- 1.6 Software for DOE -- References -- Chapter 2: Full Factorial Design 2 K -- 2.1 Why DOE -- 2.1.1 Complete Search for Solution in the Multidomain -- 2.1.2 Tremendous Reduction in the Number of Experimental Tests -- 2.2 What Is DOE -- 2.2.1 Application for DOE -- 2.2.2 Experimental Design Process -- 2.2.3 History of DOE -- 2.3 Objective Function and Goals -- 2.3.1 Quantifiable and Achievable -- 2.3.2 RSM: Regression Using DOE -- 2.4 Factors -- 2.4.1 Types of Factors -- 2.4.2 Effects of Factors and Their Interactions -- 2.4.3 Selections-Doable and Controllable -- 2.4.4 Dimensionless Format -- 2.4.5 Design Contrasts and Effects.
Fundamentals of Design of Experiments for Automotive Engineering Volume I
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)