SS507 Intermediate Level Design and Analysis of Experiments (DOE)
This intermediate level course builds on the “Intro to Design of Experiments” course. It will reinforce the concepts in the introductory course and take you to the next level of understanding to optimize your ability to choose the best designs for the diversity of situations and challenges you will confront. You will be able to lead teams in designing powerful studies of cause and effect and the discovery of solutions to complex problems or improvement challenges. You will be able to maximize the use of resources with the application of fractional factorial designs and be able to design and interpret studies of the non-linear relationships that inevitably occur at some point in all processes. You will be able to find the true optimum solution with response surface methodologies. You will learn concepts and practice the applications with live and simulated designed experiments.
What You Cover
- How to design, run, analyze and interpret full and fractional factorial designs
- How to design and interpret studies to model non-linear relationships for true optimization of products and processes
- How to recognize which designs to use for which situations
- How to make decisions about process and product design accounting for all dimensions or optimizations including maximum attainment of targets, robustness and balance of all desirable results
Who Should Attend
- People working with manufacturing or non-manufacturing processes
- Manufacturing, Process and Quality Engineers
- R&D scientists and engineers,
- Product and process development and design engineers
- Marketing and business analysts
Discounts may apply, please refer to the registration page for details.
Recommended: Introduction to Design of Experiments (SS505) or equivalent knowledge. This includes knowledge and understanding of how to design and analyze three-factor factorial experiments, basic statistical concepts such as distributions, sample statistics and the central limit theorem. Prior training in regression analysis and hypothesis testing isn’t required as the course teaches the applicable principles as part of this course; however, they provide an excellent preparation.
Principal Instructor: Steve Zagarola
Steve Zagarola is a founding member and managing partner of the Northwest Center for Performance Excellence (NWCPE). He is also founder of The ZDM Group, an organization dedicated to the advancement of statistically based approaches for competitive advantage. He graduated with a BS in mechanical engineering from Georgia Tech with post-graduate studies in Psychology and Statistics at Georgia Tech and Georgia State University. Mr. Zagarola is Six Sigma Master Black Belt with more than 30 years experience in the application of statistical and modern structured approaches to the optimization of manufacturing and transactional processes, quality systems, and R&D for industries ranging from food and beverage, plastics molding, wind energy, and advanced semiconductors. Prior to his current position with NWCPE, he served as the Director of Quality for Cascade Microtech, Six Sigma Program and Quality Manager for Vestas Wind Systems and Senior Manufacturing Manager for The Coca-Cola Company. He teaches Six Sigma, Statistical Process Control, Design of Experiments and other Statistical Quality methodologies and Process Excellence topics in four continents and in English and Spanish.
Co-Instructor: Aubrey Kendall
Aubrey Kendall is a supplier quality engineer at Vestas Wind Systems. He graduated with a BS in manufacturing engineering from Brigham Young University and an MBA from Clemson University. Mr. Kendall is a Six Sigma Black Belt with over 15 years of experience in manufacturing, quality, and engineering management in aerospace, energy, and other industries. His strong combination of technical skills and ease in communicating make him an effective trainer and facilitator.
Applies to the following certificate(s):