TAF-2 — AI dynamic control of the coffee drying process.

Soluble coffee varies in roast degree, incoming liquor concentration and sensory profile (at changeover or end of batch), while drying involves many instruments and key equipment – hard to keep output consistent with fixed settings and manual adjustment alone. AI predicts the drying outcome (moisture) and target energy use, then dynamically sets optimal operating targets for APC to execute.

- Steady moisture across products. - Lower CNG use and cost control from lower moisture variation. - Towards zero-touch operation for operators.

- TAF (Tri An Factory) operators - Operations/Production, Quality, Energy/Sustainability

- SCADA/APC data - Drying-line instruments - Moisture/density results - Product specs Note: Synthetic data could be potentially provided during the process, upon approval of the Nestlé team and in compliance with data law.

To be determined Note: Nestlé's current environment includes Microsoft Azure and Microsoft Copilot. Solutions that can work with this environment are welcome, and final integration and deployment requirements will be confirmed with the Nestlé team.