Topics: Quality, Safety & Maintenance Product development , Manufacturing processes , Design Engineering and Styling
How do you determine the root cause of a problem or identify which variable settings will make the product or process more "robust"? What if you need to gain a better understanding of a complicated system? Can you identify which variables most affect performance and obtain a well-correlated regression equation that explains how those selected system variables and their interactions affect performance?
Design of Experiments (DOE) is an excellent, statistically based tool used to address and solve these questions in the quickest, least expensive, and most efficient means possible. It's a methodology that includes steps for identifying system variables worthy of study and the ideal experiment type to execute; for setting up an organized, efficient series of tests involving various combinations of selected variables; and for statistically analyzing the collected data to help obtain definitive answers to these problem-solving and optimization challenges.
DOE is a methodology that includes steps for identifying system variables worthy of study and the ideal experiment type to execute; for setting up an organized, efficient series of tests involving various combinations of selected variables; and for statistically analyzing the collected data to help obtain definitive answers to these problem-solving and optimization challenges.
This on-demand course utilizes a blend of text, videos, and hands-on activities to help you gain proficiency in executing designed experiments. It explains the pre-work required prior to DOE execution, how to select the appropriate designed experiment to run, and choosing the appropriate factors and their levels. You'll also learn how to execute the experimental tests ("runs") and analyze/interpret the results with the benefit of computer software tools, such as Minitab.
You'll set up, run, and analyze simple-to-intermediate complexity Full Factorial, Partial Factorial, Taguchi/Robust, and Response Surface experiments both by hand and using computer software. You'll also receive an overview of Mixture experiments and information on how to install and configure a fully functional 30-day trial version of Minitab for completing practice activities and for personal evaluation. You'll gain the most value from this course by running experiments through various class exercises, with answers discussed after you've had the opportunity to execute the DOE on your own.
By participating in this on-demand course, you'll be able to:
*SAE International is authorized by IACET to offer CEUs for this course.
This course will benefit engineers involved in problem-solving, such as product design or product formulation (e.g., fluid/material composition, prepared food recipes/preparation, etc.) and/or optimization; process design and/or optimization; quality improvement efforts, such as defect elimination, warranty avoidance or similar initiatives; test engineers who wish to maximize learning of system behavior with a minimum number of tests; and technicians, analysts, and managers who support engineers in the above efforts, so they may be effective participants in DOE activities.
See the options next to the Add to Cart button for details on buying this full course package, the introductory module only, and/or the core modules that build on the introduction.
Prefer live, instructor-led training? Consider the Design of Experiments (DOE) for Engineers classroom course.
"DOE expertise is a must have for engineers who deal with data all the time, whether it's in a simulation or test, or identifying the factors which have the most influence on the experiment."
Sr. Project Engineer
Borg Warner Inc.
"This course helped me to develop a good understanding of the DOE method and to apply it to real-world applications."
Senior Research Associate
University of Windsor
"Very insightful; it definitely helped me understand the different applications/uses of the DOE techniques."
Lead Engineer, EGR system PV&V
John Deere Power Systems
Email CustomerService@sae.org, or call 1-877-606-7323 (U.S. and Canada) or 724-776-4970 (outside US and Canada).
Module 1: Introduction
Module 2: Course Materials
Module 3: Full Factorial by Hand
Module 4: Running Replicates
Module 5: Statistical Analysis and Results Interpretation
Module 6: Partial Factorial Experiments
Module 7: Taguchi/Robust Experiments
Module 8: Response Surface and Other Experiments
Module 9: Best Practices
Longer courses are divided into several components called modules. They may be purchased through the following options:
Introductory module – If you’d like only an introduction or overview of the topic, this module can be purchased as a stand-alone course.
Core modules – After completing the introductory module, you may purchase the remaining course modules as one package, without the need to repurchase the introductory module.
Full course – If you'd like to take the complete course, this purchase option includes all the course modules in one package.