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AI-based visual EOL inspection: Precision for flexible parts

In many industries, especially in automotive and electronics manufacturing, quality inspection of flexible parts presents a real challenge. Whether hoses, cables, rubber parts, or other flexible components: varying diameters, lengths, and geometries make conventional, purely manual inspection difficult. This is precisely where AI-based optical inspection comes in, combining maximum precision with significant time and cost savings.

Versatile application possibilities

A key feature of this solution is its flexibility. Thanks to advanced image processing and AI algorithms, the system can detect components of various sizes and shapes – without complex mechanical adjustments. This applies to slim cables as well as large hose-pipe combinations or injection-molded products. In addition, the system can either be seamlessly integrated into an existing automation line or operated as an autonomous stand-alone solution. Manufacturers can thus optimally adapt their quality control to their own production processes – whether in high-throughput inline operation or in single and small series, which are flexibly tested in a separate inspection station.

Self-learning systems with SOMs

The core of AI-based inspection is based on Self-Organizing Maps (SOMs), a special type of neural network. Instead of “learning” defective parts, the system exclusively compares good reference images with the current production data.

This allows it to reliably detect deviations – with an error detection rate of up to 99.7% (3-sigma rule). Another advantage is the significant reduction in manual inspections by up to 80%, which decreases both personnel costs and potential sources of error.

Advantages at a glance

The final EOL test serves to identify possible faults or defects before the product is packaged and delivered to the customer. This ensures the quality of the product.

  • Universally applicable: Suitable for different nominal diameters, lengths, and geometries of flexible parts
  • High accuracy: SOMs enable precise defect detection without relying on faulty parts
  • Time and cost savings: Up to 80% fewer manual inspection steps and shorter processing times
  • Inline or stand-alone: Flexible integration into existing production lines or as an independent inspection station
  • Reliable documentation: Component-specific inspection reports and complete traceability

Conclusion

An AI-based optical inspection for flexible parts elevates quality control to a new level: faster, more precise, and significantly more cost-effective. By combining maximum flexibility with a high error detection rate, manufacturers benefit from consistently high product quality while simultaneously reducing the need for personnel. Whether inline or as a stand-alone solution – this technology can be precisely adapted to individual requirements, providing a lasting competitive advantage.

You have individual requirements?

Our service team is happy to assist you. Use the inquiry button or simply give us a call: +49 7732 99980

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