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

• Reduced jar-to-jar weight variation by 10%
• Up to 10% savings on Nesquik powder in jars, or 101g saved from a 1kg jar
• Improved product consistency and consumer satisfaction
• Less product waste on production and packaging lines
• The trial revealed that for every ten 1kg jars produced, Nestlé saved up to 1kg jar of product—a 10% savings, using the AVEVA solutions.