Design of Experiments for Engineers and Scientists

Chapter 1: Introduction to Industrial Experimentation

• • 1.1 Introduction
• • 1.2 Some Fundamental and Practical Issues in Industrial Experimentation
• • 1.3 Statistical Thinking and its Role Within DOE

Chapter 2: Fundamentals of Design of Experiments

• • 2.1 Introduction
• • 2.2 Basic Principles of DOE
• • 2.3 Degrees of Freedom
• • 2.4 Confounding
• • 2.5 Selection of Quality Characteristics for Industrial Experiments

Chapter 3: Understanding Key Interactions in Processes

• • 3.1 Introduction
• • 3.2 Alternative Method for Calculating the Two-Order Interaction Effect
• • 3.3 Synergistic Interaction Versus Antagonistic Interaction
• • 3.4 Scenario 1
• • 3.5 Scenario 2
• • 3.6 Scenario 3

Chapter 4: A Systematic Methodology for Design of Experiments

• • 4.1 Introduction
• • 4.2 Barriers in the Successful Application of DOE
• • 4.3 A Practical Methodology for DOE
• • 4.4 Analytical Tools of DOE
• • 4.5 Model Building for Predicting Response Function
• • 4.6 Confidence Interval for the Mean Response
• • 4.7 Statistical, Technical and Sociological Dimensions of DOE

Chapter 5: Screening Designs

• • 5.1 Introduction
• • 5.2 Geometric and Non-geometric P–B Designs

Chapter 6: Full Factorial Designs

• • 6.1 Introduction
• • 6.2 Example of a 22 Full Factorial Design
• • 6.3 Example of a 23 Full Factorial Design
• • 6.4 Example of a 24 Full Factorial Design

Chapter 7: Fractional Factorial Designs

• • 7.1 Introduction
• • 7.2 Construction of Half-Fractional Factorial Designs
• • 7.3 Example of a 2(7−4) Factorial Design
• • 7.4 An Application of 2-Level Fractional Factorial Design

Chapter 8: Some Useful and Practical Tips for Making Your Industrial Experiments Successful

• • 8.1 Introduction

Chapter 9: Case Studies

• • 9.1 Introduction
• • 9.2 Case Studies

Chapter 10: Design of Experiments and its Applications in the Service Industry

• • 10.1 Introduction to the Service Industry
• • 10.2 Fundamental Differences Between the Manufacturing and Service Organisations
• • 10.3 DOE in the Service Industry: Fundamental Challenges
• • 10.4 Benefits of DOE in Service/Non-Manufacturing Industry
• • 10.5 DOE: Case Examples from the Service Industry
• • 10.6 Role of Computer Simulation Models Within DOE

Chapter 11: Design of Experiments and its Role Within Six Sigma

• • 11.1 What is Six Sigma?
• • 11.2 How Six Sigma is Different from Other Quality Improvement Initiatives of the Past
• • 11.3 Who Makes Six Sigma Work?
• • 11.4 Six Sigma Methodology (DMAIC Methodology)
• • 11.5 DOE and its Role Within Six Sigma

Chapter 12: Design of Experiments in the Service Industry: A Critical Literature Review and Future Research Directions

• • 12.1 Introduction
• • 12.2 Methodology
• • 12.3 Key Findings
• • 12.4 Critical Success Factors
• • 12.5 Essential Skills Required for Service Quality Professionals
• • 12.6 Key Lessons Learned From Designed Experiments
• • 12.7 Discussion and Implications
• • 12.8 Limitations and Directions for Further Research

Chapter 13: Design of Experiments in the Service Industry: Results from a Global Survey and Directions for Further Research

• • 13.1 Introduction
• • 13.2 Research Methodology
• • 13.3 Key Findings from the Survey
• • 13.4 Discussion and Implications
• • 13.5 Limitations and Directions for Future Research