Case.AI in action: Predicting paint performance and saving formulation time

AI is also creating new opportunities within our technical community. In our Coatings & Construction Business Group, the team has developed a data-driven approach to decorative paint formulation, using statistical modelling, design of experiments and machine learning to predict performance before samples reach the laboratory.

The work focuses on key properties such as opacity, gloss and wet scrub resistance. By analysing parameters including PVC, cPVC, pigment type, particle size distribution, fillers, binders and additives, the team has built models that deliver accurate predictions validated through cross-validation and laboratory comparison.

By refining the number of input parameters and using principal component analysis to remove redundancy, the team significantly improved accuracy. As a result, the wet scrub resistance model nearly halved its error rate, the opacity model achieved higher precision (>85%) and the gloss model also strengthened (>80%).

"AI will not replace the expertise of our formulators, instead it gives them a head start. When you can predict performance before running a full set of tests, you save time, and unlock insight and better conversations with customers."

Sami Valkama

Global Technical Director, Coatings & Construction, and Managing Director of IMCD Nordics

The models decrease testing workloads, reducing laboratorial trials by more than half and material waste by up to 60%, and shorten development cycles by two thirds. There is strong potential to expand the models to other coating types and add more performance criteria.

“This work shows the real value of combining data and technical understanding,” says Sami Valkama, Global Technical Director, Coatings & Construction , and Managing Director of IMCD Nordics.

The team sees growing opportunities to collaborate more closely with principals and customers to enhance raw material understanding and continue improving model accuracy.

Digital excellence

As we look ahead, we will keep building on our unified platform, expanding AI responsibly and developing tools that make it easier for all our stakeholders to connect, share knowledge and find the right solutions. Winning together means creating the conditions for better conversations, stronger partnerships and smarter decisions across the entire value chain. Our digital ecosystem helps us do exactly that.

AI in action: Predicting paint performance and saving formulation time

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