Half the Lab Work, Same Paint Performance
Transforming Coatings R&D with AI
Fifty-six percent fewer physical formulation trials. Same paint performance. That's what MaterialsZone helped a leading European raw materials supplier achieve when reformulating two decorative paint lines using AI-Guided R&D.
The challenge? Multidimensional optimization, replacing key raw materials while maintaining strict specifications for opacity, gloss, scrub resistance and crack resistance. Traditionally, this would require extensive laboratory experimentation and testing, with every iteration consuming valuable time and resources.
MaterialsZone enabled scientists to take a different approach.
Using the customer's historical formulation and experimental data, the MaterialsZone platform applied machine learning to predict formulation performance, identify promising alternatives and guide scientists to execute only the most valuable experiments.
Each new laboratory result fed back into the system, continuously improving predictions and helping teams make smarter decisions with fewer trials.
The impact went beyond faster reformulation. In a related cost-optimization project, an AI-guided formulation achieved approximately 10% lower formulation costs, while meeting performance requirements.
For paints and coatings manufacturers, this approach opens opportunities to respond faster to raw material shortages, regulatory changes, specific customer requests and cost pressures without compromising quality.
Want to see AI-Guided R&D in action? Register for MaterialsZone's coatings webinar to explore real-world applications and results.
Looking for a reprint of this article?
From high-res PDFs to custom plaques, order your copy today!
