Design of Experiments

This practical and hands-on session introduces attendees to the power of practical multi- variable experimental design approaches. Attendees who successfully master these approaches commonly gain a 50% improvement in the efficiency and effectiveness of their test protocols. Experimental design is the premier tool to quantify interactions between variables...frequently a key root cause of process and product design anomalies.

Class Details

Class Name:
Design of Experiments
This course is designed for process engineers, quality engineers, technicians, design engineers and managers who are designing new products or processes as well as optimizing new products or processes.
2 Day Course

Learning Objectives

  • Ability to set full and fractional-factorial designs using software
  • Conduct graphical and simple statistical analysis of experimental design data using software
  • Understand the importance of using engineering and scientific knowledge to select application factor ranges, levels, and energy related responses
  • Utilize software so as to determine variance reduction factors as well as those that shift the mean
  • Co-optimize multiple responses using desirability functions
  • Aware of the need to conduct confirmation trials to verify simple model predictions

Outline At-a-Glance

Day One:

  • Introductions, Goals, Expectations
  • The Need for Experimental Design in Industry
  • Why Engineers, Technicians and Scientists Need to Use These Powerful Approaches
  • Examples of Applications from Industry
  • What is an Experimental Design?
  • What are the Benefits?
  • Different Experimental Objectives
  • Screening Approaches vs. Modeling Approaches
  • Why Conduct an Orthogonal Array?
  • Graphical Analysis
  • Contour Plots
  • RSM Plots

Day Two:

  • Blending Experimental Design with Knowledge of the Technology
  • Checklist of Detailed Planning Questions
  • Common Pitfalls for Those New to Design of Experiments
  • Analysis for Variance Reduction
  • Full-Factorials, Fractional-Factorials, Taguchi Arrays
  • ANOVA and MLR Using Software
  • Numerous Examples Using Software
  • Rules of Thumb regarding Set-up and Analysis
  • Multiple Response Co-optimization Using Desirability Functions
  • Group Exercise using Statapult

Job Roles