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Design of Experiments (DOE)

All of our training courses and programs are "hands-on", and are offered at the client's facility (on-site), anywhere in the world.
Course Description
This course provides an in-depth understanding of how to plan, design, conduct and analyze experiments (DOE). It starts with basic single-factor designs, and includes factorial, screening design, Plackett-Burman, fractional factorials, and finally Taguchi's Orthogonal Arrays. This comprehensive course teaches you the concepts, as well as interpretation and analysis of your experimental data.

All examples are based on industrial applications by the author. Once you learn the DOE concepts presented in our step-by-step logical approach, you will be able to use any software package. Demonstrations will be done using Minitab®.

Design of experiments is a must for individuals involved in all aspects of product and process development, characterization and optimization.

Course Highlights We Wrote the Book
    Why Statistical Experimentation
    Fundamental Statistical Methods
    Disadvantages of One-Factor-at-a-Time Experiments
    One Factor Experiments, t-test, Chi-Square tests, F-test
    Anova - Analysis of Variance
    Factor Selection (Independent Variables)
    Selecting Responses (Dependent Variables)
    Factorial Design, Full Factorial Design
    Main & Interactive Effects
    Single Replicate & Replicated Analysis
    Yates Algorithm
    Randomization and Blocking Techniques
    Normal Plots and Residual Analysis
    Accounting and Reducing Variation
    Fractional Factorial Design
    Confounding and Aliases
    Contrasts, Generators and Resolution of Designs
    Folding, Dropping Factors, Grouping Factors
    Single Replicate & Replicated Analysis
    Polynomial Modeling, Regression Analysis
    Factor Screening Design Experiments
    Saturated Designs
    Plackett-Burman Designs
    Taguchi's Orthogonal Arrays & S/N Ratios
Duration: Typically 3 to 4 days.
Book: Design of Experiments

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We are Proud of Our "Hands-On" Training Approach
We take participants through lectures in which they learn the tools, methods, and concepts. Then, we help them to apply the tools to their own processes.

This is, by far, the most efficient way to learn design of experiments.