Hosted by: Assoc. prof. Audun Formo Buene, NTNU, in collaboration with Bayer

Instructor: Volker Kraft, Ph.D., JMP Academic Ambassador

Audience: Students, engineers, scientists and technicians involved in characterizing, evaluating and improving processes and systems

Duration: October 1st 2026, 9.15-16.00

Location: Meeting room D3-114 Onsager (How to get there? Mazemap link)

To estimate coffee demand and to receive installation instructions prior to the workshop, please register by sending an email to audun.f.buene@ntnu.no.

 
This free workshop is open to NTNU teachers, researchers and students who want practical skills in design of experiments (DOE). DOE is one of the most in-demand skill sets in industry — companies like Bayer rely on it daily to develop and optimize products and processes — yet it's still underrepresented in most curricula. This workshop closes that gap.
 
Designed experiments are the only reliable way to establish cause and effect between inputs and outputs. Unlike analyzing existing data, DOE lets you explore new factor spaces, drive innovation and test opportunities systematically — and JMP makes this accessible without any programming. Beyond classical designs, JMP's custom design capability tailors your experiment to the exact question you're asking, without wasting resources.
 
You will:

• understand why DOE matters, with a recap of ANOVA and regression

• compare classical and optimal designs

• design, analyze and interpret screening experiments, including Definitive Screening Design

• design, analyze and interpret response surface experiments

• augment designs for sequential experimentation

• apply robust optimization

• evaluate and compare designs

Extra topics (on-demand): Blocking, split-plot designs, covariates, mixtures; Functional (e.g. spectral) data analysis; Bayesian optimization 
 
The day mixes concept presentations, live demos and hands-on exercises. Examples come mainly from chemistry and biostatistics but carry over easily to materials science, agri-food science and engineering.
 
You need to:

• Bring a laptop with JMP Student Edition 19 installed (free at JMP.com/student for Windows and Mac). No prior knowledge required — all materials and demos will be shared with participants.