Real-Time Welding Optimization with Welding Robot
Technology Category
- Analytics & Modeling - Digital Twin / Simulation
- Analytics & Modeling - Predictive Analytics
Applicable Industries
- Equipment & Machinery
- Metals
Applicable Functions
- Discrete Manufacturing
Use Cases
- Condition Monitoring
- Digital Twin
- Predictive Maintenance
- Predictive Quality Analytics
Services
- Data Science Services
- Software Design & Engineering Services
- System Integration
About The Customer
Manufacturing of pressed sheet metal parts in the automotive industry.
The Challenge
Automating welding processes with robots enhances productivity and environmental friendliness. However, the quality of robotic welding can deteriorate due to various factory conditions. Continuous monitoring and adjustments are necessary to maintain high standards.
The Solution
TEKNOPAR integrated data from multiple sensors, including microphone and vibration sensors, environmental sensors, fiberoptic laser sensors, and Magmaweld devices, to create a comprehensive real-time monitoring system. Advanced regression models analyzed these data streams to detect potential quality issues, allowing immediate adjustments to the robot's parameters.
Data Collected
Acceleration, Humidity, Microphone, Pressure, Temperature
Operational Impact
Quantitative Benefit
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