ai for manufacturing paints & coatings

AI-Driven Product Analysis

In paint manufacturing, pH, color and viscosity specified by clients are challenging to meet because of irreducible variability in production conditions, thereby reducing output consistency. A substantial percentage of the stock mixtures requires multiple rounds of adjustments to meet requirements, resulting in significant waste, additional cost, profit reduction, lower productivity and delivery delays. Our AI solution solves these issues.

pH/viscosity prediction accuracy
estimated reduction in production time
estimated cost savings per plant, annually

An AI solution (currently in beta)

Cognistx uses a variational deep learning model designed for large scale, real-world paint and coatings production. Chosen from >50 alternative models, our algorithm accommodates highly dimensional and non-linear sequential data on >2000 raw material and multiple plant conditions.

Our architecture accommodates irreducible test errors, detection limits as well as highly dimensional, non-linear sequential data on thousands of raw materials and production conditions.

By improving the manufacturing process, our AI solution is expected to save between $500K - $1M per plant, annually.

AI-Driven Decision Support


Raw material properties, plant conditions and final product requirements data is input into the system


Cognistx data engine cleans and transforms the data


Machine learning engine suggests optimal raw material mix for human feedback


Self-tuning engine remembers and automatically improves model from human feedback


System dashboard displays real-time production performance matrix for human inspection

The Result:

Improved Quality Control, Reduced Cost, Increased Production Capacity for Plants