GEA manufactures and installs milking robots in dairy farms to automate milk extraction from cows. Each robot continuously logs operational data like milking time, cleaning time, and machine status and stores on a local server at the farm. As the deployment footprint grew, GEA required a scalable mechanism to collect this data across all farm sites and put it in front of the right people. This engagement delivered an end-to-end data harvesting, processing, and analytics platform to do exactly that.
GEA is a global leader in processing technology, supplying advanced equipment and components to the food, beverage, pharmaceutical, and allied industries. The group specialises in sophisticated production processes, offering a comprehensive portfolio that spans machinery, industrial plants, process technology, and end-to-end services, including their connected milking robot systems deployed across dairy farms.
Milking robots at each farm continuously generate performance data, but that data was siloed on local servers with no way to extract, consolidate, or analyse it centrally. GEA had no process to harvest this data at scale, which meant machine performance could only be assessed manually and on-site.
The core requirement was a mechanism to collect performance data from every connected farm, process it reliably, and surface it in a way that allowed GEA and their farm customers to evaluate machine health, track operational metrics, and identify malfunctions or underperformance before they escalated.