Eigen Success Story – Plastic Welding
A leading global automotive supplier was relying on sample destructive testing to ensure quality standards were being met on a critical welding process. The random nature of this testing exposed them to significant recall risk. It engaged Eigen to help them see better welds.
The following is a brief summary of how Eigen helped this manufacturer replace destructive testing with proactive detection and prevention.
Before – Destructive Testing
- Quality Engineers were manually destructing sample parts each shift to test weld thickness.
- Testing required 1 hour per shift plus the cost of the destructed product.
- Lagging quality metrics did not allow Process & Quality Engineers to detect or troubleshoot issues in-process.
- Disparate quality data resulted in multiple meetings/days to determine root cause when the OEM escalated an issue.
After – Eigen Image and Process Monitoring
- FLIR thermal cameras captured various views of the weld process and were used to generate a virtual part image for part-to-part monitoring.
- Eigen Machine Learning specialists designed a monitoring algorithm that predicted weld thickness to replicate real-time quality testing for all tanks post welding process.
- Insights generated from correlated image and process data delivered through Eigen’s online platform streamlined troubleshooting and root cause investigations.
- Manufacturer adopting Eigen’s platform across NA operations and updating control plan with OEM to replace manual quality assessment processes with Eigen’s automated system.
If you’d like to learn more about how Eigen can help you prevent costly defects in your plastic welding process, contact us today.