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
Audience:
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.
Duration:
2 Day Course
Language:
English

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