Speaker
Description
Design of Experiments (DOE) is a powerful tool for optimizing industrial processes with a long history and impressive track record. However, despite its success in many industries, most businesses in Denmark still do not use DOE in any form due to a lack of statistical training, preference for intuitive experimentation, and misconceptions about its effectiveness.
To address this issue, the Danish Technological Institute has developed Brownie Bee, an open-source software package that combines Bayesian optimization with a simple and intuitive user interface. Bayesian optimization uses a more iterative approach to solve DOE tasks than classic designs but is much easier for non-expert users. The simple interface serves to sneak Bayesian optimization through the front door of companies that need it the most, particularly those with low digital maturity.
In this talk, I will explain why Bayesian optimization is an excellent alternative and supplement to traditional DOE, particularly for companies with minimal statistical expertise. During the talk, I will showcase the tool Brownie Bee and share insights from case studies where it has been successfully implemented in 15 Danish SMEs.
Join me to discover how you can incorporate Bayesian optimization through Brownie Bee into your DOE toolbox for process optimization and achieve better results faster compared to traditional DOE designs.
https://www.browniebee.dk/
| Classification | Both methodology and application |
|---|---|
| Keywords | Bayesian Optimization, DOE, case-studies, open-source |