Design of Experiments for Engineers and Scientists

Design of Experiments for Engineers and Scientists

2nd Edition - February 22, 2014

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  • Author: Jiju Antony
  • Hardcover ISBN: 9780080994178
  • eBook ISBN: 9780080994192

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The tools and techniques used in Design of Experiments (DoE) have been proven successful in meeting the challenge of continuous improvement in many manufacturing organisations over the last two decades. However research has shown that application of this powerful technique in many companies is limited due to a lack of statistical knowledge required for its effective implementation.Although many books have been written on this subject, they are mainly by statisticians, for statisticians and not appropriate for engineers. Design of Experiments for Engineers and Scientists overcomes the problem of statistics by taking a unique approach using graphical tools. The same outcomes and conclusions are reached as through using statistical methods and readers will find the concepts in this book both familiar and easy to understand.This new edition includes a chapter on the role of DoE within Six Sigma methodology and also shows through the use of simple case studies its importance in the service industry. It is essential reading for engineers and scientists from all disciplines tackling all kinds of manufacturing, product and process quality problems and will be an ideal resource for students of this topic.

Key Features

  • Written in non-statistical language, the book is an essential and accessible text for scientists and engineers who want to learn how to use DoE
  • Explains why teaching DoE techniques in the improvement phase of Six Sigma is an important part of problem solving methodology
  • New edition includes a full chapter on DoE for services as well as case studies illustrating its wider application in the service industry


Manufacturing engineers, project engineers, quality engineers, quality managers, production engineers and students

Table of Contents

  • Preface


    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



    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



    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



    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



    5. Screening Designs

    5.1 Introduction

    5.2 Geometric and Non-geometric P–B Designs



    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



    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



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

    8.1 Introduction



    9. Case Studies

    9.1 Introduction

    9.2 Case Studies


    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



    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



Product details

  • No. of pages: 220
  • Language: English
  • Copyright: © Elsevier 2014
  • Published: February 22, 2014
  • Imprint: Elsevier
  • Hardcover ISBN: 9780080994178
  • eBook ISBN: 9780080994192

About the Author

Jiju Antony

Jiju Antony is a professor of Industrial and Systems Engineering and certified LSS Master Black Belt in the department of Industrial and Systems Engineering at Khalifa University, Abu Dhabi, UAE. He has a proven track record for conducting internationally leading research in the field of quality management, quality engineering, continuous improvement, and operational excellence. Professor Antony has authored over 500 journal, conference, and white papers; 14 textbooks; and two conference proceedings. He is the Editor in Chief of the International Journal of Lean Six Sigma, Editor in Chief of the International Journal of Quality and Reliability Management, and Associate Editor of the TQM Journal and BE Journal. Professor Antony has worked on a number of consultancy projects with several blue-chip companies such as Rolls-Royce, Bosch, Siemens, Parker Pen, Siemens, Johnson and Johnson, GE Plastics, Ford, Scottish Power, Tata Motors, Thales, Nokia, Philips, General Electric, NHS, Glasgow City Council, ACCESS, Scottish Water, Police Scotland, university sectors, and a number of small- and medium-sized enterprises.

Affiliations and Expertise

Professor of Industrial Systems Engineering, Department of Industrial Systems Engineering, Khalifa University, Abu Dhabi, UAE.

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  • MehdiLalpoor Sat Jan 05 2019

    Perfectly delivered on time. I

    Perfectly delivered on time. I recommend the book for design of industrial experiments.