Global Food and Beverage Manufacturer Applies Industrial AI and Predictive Analytics to Optimize Quality and Yield

Initiative

Eliminate manual variability in the agglomeration process. Nestlé sought to digitize expert operator knowledge, transitioning from lagging lab samples to real-time predictive control to stabilize product density and moisture levels.

Solution

• AVEVA Data Hub
• AVEVA Advanced Analytics
• Digital Twins
• Digital Threads
• Perfect Quality Solution

Action

Recommendations across multiple controllable variables were integrated into Startup and In-Run work processes. Using standardized views, operators monitored and optimized product density, moisture, and quality in real time.

Value Attained

• Process Control: Reduced jar-to-jar weight variation by 10% with consistent standard deviation.
• Operational Efficiency: Increased throughput by ~400 lbs/hr and significantly reduced fines recirculation
• Waste Reduction: Achieved near-zero waste in collection "socks" during trials.
• Workforce Augmentation: Empowered operators with real-time guidance to consistently deliver optimal product "fluffiness."