Case Study: General Electric boosts capacitor yield with FogHorn edge intelligence

GE Detects Early Defects and Improves Capacitor Production Yield with Edge Intelligence

General Electric (GE), the world’s largest digital industrial company, was struggling with hard-to-detect capacitor failure conditions that were reducing yield and driving up scrap costs across its manufacturing operations. To gain real-time insight into data from 30+ machines and multiple production stages, GE worked with FogHorn and its edge intelligence platform, including FogHorn VEL and EdgeML.

FogHorn implemented an edge analytics solution that combined machine sensor data and RFID streams to monitor processes in real time, automate quality checks, and provide early defect detection at the edge. The system was deployed across 35 machines, 13 processes, and 33 RFID readers, helping GE increase yields by 8% while reducing scrap and bandwidth usage compared with a cloud-only approach.

General Electric