Case study · September 25, 2023

Results after four adaptations with partner Adler Lacke

PI Probaligence and ADLER-Werk Lackfabrik reached commercial-grade color matching results after only four adaptations in September 2023, using PI's own machine learning algorithms and adaptive experimental design within the Smart Paint Factory Alliance.

Benchmark table listing ten RAL and NCS reference colors with their color difference (dE) values, comparing commercial color matching software against the best of four machine learning trials.
Color difference (dE) after four ML adaptations, compared with commercial color matching software using standard formulas.

Scroll sideways to read the labels.

Within the Smart Paint Factory Alliance (smartpaintfactory.com), together with ADLER-Werk Lackfabrik (adler-lacke.com), we used our own machine learning algorithms and methods for adaptive experimental design for color matching. After only four adaptations, we came very close to, and in part even better than, the results of commercial color matching software using standard formulas.

Our big advantage: color is not the only thing that can be optimized. Everything that can be measured can go into the optimization.

  • Opacity, gloss, and viscosity.
  • Abrasion resistance.
  • Manufacturing costs.

Ideally the process parameters are optimized at the same time. That is exactly what our research project Na, Logisch works on, and where we keep improving the methods.

Next step
Solution
AI for Paint and Coatings

Where this fits in formulation and coating R&D.

Guide
Match a color in two batches, not seven

Adaptive experimental design on a formulation target.

Interactive demo
Try to beat STOCHOS

Three use cases, about two minutes each.

NewerGreen Tech kick-off event for project Na, Logisch

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Partners, customers, and research collaborators
AnsysCADFEMSimuTech GroupMEScoTSNEBoschZFGEMUDLRAdler LackeMankiewiczDuluxPlixxentFraunhoferHochschule NiederrheinFUELL Lab AutomationHumotionUniversitaet HamburgRobert Bosch Stiftung