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DOE Program 1: Design of experiments

DOE Program 1: Design of experiments


Available Course locations & dates

Program 1 - $99.00 USD
Program 1 + Exam - $199.00 USD


MKS Data Analytics Solutions invites to an open on-demand training course for researchers, scientists and engineers. Duration of the training is Q1 2017.

Why do we need design of experiments (DOE)? Understand what DOE is and what makes it so useful. Attend this training and learn about the fundamental uses of DOE (screening, optimization and robustness testing) and how these applications can maximize the information content in your data. Find out how quality-by design (QBD) and design space estimation may help you discover a robust setpoint for your system or process at which there is a low risk of failing to comply with response specifications.

The on-demand training is available through a series of two programs of 6 + 6 recorded webinars. The programs are composed of lectures and MODDE software demonstrations built on real-life datasets. Written hands-on computer exercises are also part of the course documentation. There will be 3 Q&A sessions where the course participants can have live interaction with the trainer.

Optionally, the course delegate may take part of an exam for each course program. Certification is provided for all participants who successfully complete the training and the exams.

The two programs and the Q&A sessions are the following:

Program 1: Design of experiments (DOE), what it is, and how it can be applied to efficiently solve your problems (6 recorded webinars)

Program 2 – Accomplishing reliable Quality-by-Design (QBD) using MODDE´s robust optimization and design space estimation technology (6 recorded webinars)

Q&A session 1:
Wednesday February 8, 3pm – 4pm (CET); focus on DOE&QBD Program 1

Q&A session 2:
Wednesday March 1, 3pm - 4pm (CET), focus on DOE&QBD Program 2

Q&A session 3:
Wednesday March 22, 3pm - 4pm (CET), wrap-up of the entire DOE&QBD course

Registration links will be sent out once payment is recieved.

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