Fast Track
If you're flexible with travel, jump ahead by selecting one of the recommended facilities to the right.
Otherwise, the form below helps drill down from state to city to a specific training facility for your Design of Experiments (DOE) Training class.
Recommended States
Pre-enrollment is accepted until the minimum student requirement is met.
Once enough students have signed up, then we will reach out to process your payment.
If minimum enrollment is not attained, we may ask that you consider an alternate date or location.
With that in mind, would any of the 4 states be possible for you?
Facilities in these states either have a low minimum student requirement, or already have students signing up:
All States
However, if travel is a limitation for you and none of the states above will work, don't worry. We have several options.
And if none of those below suit your needs, feel free to contact us and make a request.
We will do everything possible to accomodate.
A common request we receive is to do on-site training for companies seeking to get several employees trained at the same time.
About Design of Experiments (DOE) Training
Who is Design of Experiments (DOE) Training for?
Design of Experiments can be used by anyone wanting to improve a service, process, or product. If the situation can be represented or modeled as a system with an output driven by inputs all of which can be measured, and inputs can be set at different levels, then DOE training is for you. In our course, students learn:
Design of Experiments (DOE) Training Course Overview:
We regard Design of Experiments (DOE) as the most powerful root cause analysis tool in the world. Our Masters have used DOE to produce 6-digit per year savings many times across a broad range of industries and applications. It's definitely worth adding to your arsenal. DOE can optimize product design when seeking to improve some performance criteria influenced by component dimensions or general features. By setting these features to varying, measurable levels, their relative influence on the response and preferable settings can be determined. Similarly, DOE can optimize process design when seeing to improve a process output influenced by process inputs. Even soft inputs like shift A,B,C can be used. Defect rate is commonly the process output, but many others such as operating cost can be used. From a service perspective, employee satisfaction would be an HR example. To domenstrate this, our class uses a fun case study providing a real, physical system allowing students to actually experience how DOE works. Advanced topics such as fractional factorial arrays, multi-level factors, Taguchi arrays, etc. are covered. Statistical software such as Minitab or SigmaXL is also used.
