Company Case Study | Decoding the mysteries of powder processing: What’s your solution?

This session will be recorded on site and will be made available for on-demand viewing from 8th December 2025 till 16th January 2026.

Amid raw material shortages, rising costs, and the need for extended shelf life, saving time and resources in evaluating alternative ingredients is a key differentiator. In the complex world of powder formulations, Omya has developed a predictive tool that forecasts long-term caking behavior using short-term lab tests.

Combining moisture sorption isotherms, powder rheology, and data analytics, the approach – validated in milk powders and now applied to other powders – shows just a 1% margin of error compared to six-month shelf-life data. Results demonstrate the predictive power of quick lab assessments, offering R&D teams a faster, data-driven approach to forecast powder performance.

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