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MONITECH

Implementation of AI based EV Battery Welding Quality monitoring system

Development time

7 Month

Manpower

4 Professionals

The Brief

The demand for quality information of various welding methods is increasing in line with the trend of new material welding, the increase of micro and ultra-precision products, and the increasing demand for eco-friendly and energy-saving welding processes. In particular, the MONITECH team wanted to implement AI technology, in order to establish a high-precision welding monitoring system for guaranteed laser welding quality of lithium-ion batteries, which are exploding in demand along with the rapid growth of the electric vehicle market.

Services

Welding Quality monitoring
AI algorithm development

Dashboard
Visualization

1

2

3

4

5

Data Collection
&Modelling

API based
integration system

Maintenance

Technological

Challenges

The laser/Ultrasonic welding monitoring system should deliver accurate and constant quality analysis from various power sources

Reliable Quality Monitoring

Combining Monitech’s knowhow on exiting quality monitoring methods and Ellexi’s Confusion Matrix analysis on various sensor data, such as UV, IR, light, high-speed thermal image, to secure high defect detecting precision and minimize false alarms

Multi-sensor compatibility

Overcome limitations of statistical and wavelength data analysis on multi-sensor (optical+thermal, vision+thermal and etc.) configured quality monitoring system by applying deep learning technology

Platform with Scalability

Provide modulation of AI models by its welding method (arc, spot, ultrasonic, laser and etc) and RestAPIs for interoperability

Roadmap

API based integration system

  • Anomaly Pattern Detection

  • Anomaly Pattern Detection

  • Anomaly Pattern Detection

Maintenance

  • Anomaly Pattern Detection

  • Anomaly Pattern Detection

  • Anomaly Pattern Detection

AI algorithm development

  • Anomaly Pattern Detection

  • Anomaly Pattern Detection

  • Anomaly Pattern Detection

Dashboard Visualization

  • Anomaly Pattern Detection

  • Anomaly Pattern Detection

  • Anomaly Pattern Detection

Key

Multi-sensor compatibility

Overcome limitations of statistical and wavelength data analysis on multi-sensor (optical+thermal, vision+thermal and etc.) configured quality monitoring system by applying deep learning technology

The Result

1

Welding Results Recall above 90%
EV battery manufacturing process BMA line lead welding recall performance 99.8%

2

Welding result Welding Results Recall above 90%

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