Design of Experiments and Validation of Solutions in Six Sigma


Overview/Description
Target Audience
Expected Duration
Lesson Objectives
Course Number



Overview/Description
"We are, I think, in the right road of improvement, for we are making experiments," said Benjamin Franklin. In the Improve stage of the DMAIC process, Six Sigma teams design and conduct experiments to study the nature of relationships between input variables and the response variable(s). They do this by controlling and changing the input variables and observing the effects on the response variable(s). After determining what and how much needs to be changed to meet the desired improvement, teams generate solution ideas to optimize the response, and then the ideas are tested, implemented, and validated. Later in the control stage, efforts are made to keep the improved processes, products, or services under statistical control and to retain the gains. This course explains the basic design of experiments (DOE) concepts and outlines how to select, test, and validate improvement solutions in the final stages of a Six Sigma project. During the course, basic DOE concepts such as factors, levels, interactions, and main effects are introduced. The course also explores the full and fractional factorial designs and the DOE process. In addition, it teaches how to select, test, and validate solutions using a variety of analysis, screening, and testing tools commonly used in Six Sigma. This course is aligned with the ASQ Certified Six Sigma Green Belt certification exam and is designed to assist learners as part of their exam preparation.

Target Audience
Candidates seeking Six Sigma Green Belt certification; quality professionals, engineers, production managers, and frontline supervisors; process owners and champions charged with the responsibility of improving quality and processes at the organizational or departmental level

Expected Duration (hours)
1.5

Lesson Objectives

Design of Experiments and Validation of Solutions in Six Sigma

  • match the key elements of the DOE methodology with examples
  • match each type of DOE with an example
  • distinguish between full and fractional factorial DOEs based on the number of runs, factors, and levels for each
  • sequence examples of the steps in the DOE process
  • identify examples of interactions and main effects in DOE
  • match tools that are used to identify improvement solutions with descriptions
  • identify how to evaluate and select solutions using a solution selection matrix
  • recognize when to use various tools for testing and validating improvement solutions
  • Course Number:
    oper_09_a01_bs_enus