Unser Vortrag zeigte, wie Künstliche Intelligenz neue Wege in der Lackentwicklung eröffnet. Angesichts von Rohstoffvariabilität, strengeren Umweltauflagen und der Notwendigkeit nachhaltiger Prozesse sind innovative Ansätze gefragt.
Our talk highlighted how Artificial Intelligence opens new pathways in coatings development. With raw material variability, stricter environmental regulations, and the urgent need for sustainable processes, innovative approaches are essential.
AI-based methodology for adaptive experimental planning:
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Unlike classical, predefined experimental design, our approach enables dynamic, data-driven steering of experiments.
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Parameters from raw materials, application, and processes are integrated into probabilistic AI models (STOCHOS).
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The AI proposes targeted, optimal experiment combinations, reduces the number of trials, and avoids inefficient or incompatible setups.
The benefits:
✔️ Significantly lower resource consumption and time investment
✔️ Facilitated transition to sustainable raw materials
✔️ Prototype validation on high-throughput and industrial-scale equipment
✔️ Presentation of our software solution for AI-driven experimental planning
A special thank you to our project partners: AOM-Systems GmbH, Mankiewicz Gebr. & Co., Füll Lab Automation GmbH, HS Niederrhein, and Fraunhofer IFAM.
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