Price: $849.50

Length: 1 Day
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Design of Experiments Training, DOE Training Overview for Managers

Why TONEX’s Design of Experiments Training? DOE Training Course Description

The Design of Experiments training course for managers covers a brief yet thorough training on how to use DOE techniques to analyze causes of failures, resolve problems and issues, and improve and optimize processes.

Through this short workshop, you will learn the principals and applications of the DOE. You will receive sufficient amount of training to be able to identify critical input factors that can have significant impacts on the process outcome. This hands-on training course supplements basic statistics and conventional experimental designs, which can be applied in both designing new products and process and improving and optimizing the existing products and processes.

Through this hands-on brief workshop, trainees will also learn about:

  • Overview of principals: theory of the systems, variation, and basic principals of statistics methods
  • Historical background of DOE
  • Advantages of DOE over traditional methods of experimentation
  • Factorial designs
  • Fractional (partial) factorial and Plackett-Burman
  • Procedure of executing DOE

During this introductory training of DOE, you will learn the basics of experimental design and their role in statistical process control. Even if you don’t have a strong background in math and mathematics, don’t worry. Our instructors at TONEX will teach you how to set up and run basic factorial and screening experiments; how to analyze the experimental results; and determine the crucial factors for more investigations. Once you become comfortable with these fundamentals, our instructors will help you design and execute experiments step by step.


The introduction to Design of Experiments (DOE) training is a 0ne-day course ideal for managers, scientists, technicians, production personnel, products/processes designing people, and the R&D team.

Training Objectives

Upon the completion of this seminar, the attendees are able to:

  • Understand the concepts, principals, applications, and advantages of DOE
  • Develop the skills and capabilities required in order to set up, conduct, and analyze a DOE
  • Use DOE for problem-solving, root-cause analysis, optimization, products/process designs
  • Understand and interpret the DOE results
  • Execute DOE test matrix completely
  • Construct DOE models
  • Use ANOVA, regression, or graphical methods to analyze the DOE results
  • Identify those input factors that have the most impact on the outcome
  • Exploit confounding concepts to interpret fractional factorial DOE
  • Understand Robust DOE
  • Select appropriate Response Surface Design

 Course Outline


  • Goals and objectives
  • The need for DOE
  • Why experimental design is necessary?
  • Basic terminologies
  • Purposes of experiments: screening, troubleshooting, robustness, modeling
  • Orthogonal arrays, definition and advantages

How To Construct A DOE

  • Define response variables
  • Define input factors
  • Choose a proper design
  • Select a statistical approach (model)
  • Running
  • Evaluating the selected design elements

Steps To A Successful DOE

  • Choose appropriate responses based on the technology
  • Full-factorial, fractional factorials, and Plackett-Buman arrays
  • Design resolution
  • Taguchi table

The DOE Analysis

  • Evaluating and adjusting the statistical model
  • Manipulating the response variables
  • D-optimal arrays
  • Graphical analysis
  • ANOVA method
  • Multiple response optimization
  • Categorical responses analysis

Designs Supplementations

  • Additional running
  • Extrapolations
  • Aliasing and confounding
  • Principals of robustness
  • Regression analysis

Response Surface Experiments

  • Central composite designs
  • Box-Behnken arrays
  • Multilevel factorials
  • Mixed experiments


Design of Experiments Training, DOE Training Overview for Managers

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