FogHorn > Case Studies > GE Detects Early Defects and Improves Capacitor Production

GE Detects Early Defects and Improves Capacitor Production

Technology Category

Analytics & Modeling - Real Time Analytics

Applicable Industries

Renewable Energy

Services

Data Science Services

The Customer

General Electric Company

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About The Customer

General Electric Company operates as a digital industrial company worldwide. It operates through Power, Renewable Energy, Oil & Gas, Aviation, Healthcare, Transportation, Lighting, and Capital segments. The Power segment offers technologies, solutions, and services related to energy production, including gas and steam turbines, engines, generators, and high voltage equipment; and power generation services and digital solutions. General Electric Company was founded in 1892 and is headquartered in Boston, Massachusetts.

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The Challenge

Hard to Detect Capacitor Failure Conditions Reducing Yield, Increasing Scrap

GE was facing multi-million-dollar scrap problems due to limited real-time insights into the entire production process. They believed they could significantly improve the yield and reduce the scrap of their manufacturing operation by analyzing a large amount of RFID sensor data being produced by 30+ machines during the production cycle. This included correlating processing data in real-time from several sources to create an edge intelligence layer with FogHorn for real-time condition monitoring throughout the production process. The goal was to identify defects early, quickly determine the root cause, and speed remediation actions to improve yield and reduce scrap costs.

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The Solution

FogHorn Edge Intelligence Senses Defects Early in Production Cycle, Improving Yield, Reducing Scrap

To solve its multi-million-dollar scrap problems, GE asked FogHorn to apply its analytics expertise to help improve manufacturing yields. FogHorn developed a solution using its complex event processor to transform raw, streaming machine data combined with RFID into actionable parts and process quality characteristics.

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Operational Impact

[Data Management - Real Time Data]
- Real-time edge testing at each stage of manufacture for improved yields and reduced scrap
- Continuous process improvement by providing real-time analytics to OT staff
- Smart, rather than scheduled, maintenance of manufacturing equipment to maximum uptime

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