Statistical Design of Experiment (DoE) is THE tool to minimize the number of experiments necessary to determine the best possible process parameter settings. Thus, it is a procedure for the design of experiments which calculates that all experimental results are superimposed by unavoidable random errors. These random errors are taken into account using statistical methods not only during evaluation, but also during the design of experiments, i.e. before the often lengthy and cost-intensive experimental phase begins.
The event presents practical application examples from the fields of engineering, the chemical industry and paint formulations. It will be shown how the Statistical Design of Experiments specifically finds an optimum in the process, that usually only a few experiments are necessary for this. In addition, the detection and handling of interactions as well as the simultaneous optimization of several target variables will be explained.
The participation fee is 138,00€ (net)
16.04.2021
Speakers of the presentationsHere you can see the speakers who will give the presentations at the event.
Dr. Dirk Jödicke
- Company
- Coaching & Prozessoptimierung
- Information
- Dirk Jödicke studied chemistry in Bochum and Oviedo (Spain). After taking a doctorate in Organic Chemistry, he began his professional career in the sheet glass industry. In laboratories, pilot plants and production facilities in this industry, he worked on innovative glass and plastic composite systems, thin semiconductor films, lithium-ion conductive polymers, electrochromics, photochromics and other systems to exploit variable properties in glass for architectural and automotive applications. Numerous inventions subsequently led to the successful market launch of so-called intelligent windows with variable light transmission. Dirk Jödicke was Head of Research and Development and Head of Quality Assurance, and as a Six Sigma Master Black Belt he is now a freelance consultant for Six Sigma in statistical data analysis, statistical design of experiment, and process optimization.