case study
Insightful Quality Control
Necessary information /
Context / Client information
Our client Dormer Pramet, the global manufacturer and supplier of tools for the metal cutting industry, faced a quality control problem. Their complex manufacturing process relied heavily on manual inspections, leaving the risk of undetected defects until a final inspection or even worse – by the customer.
Tens of thousands of inserts with various features made thorough inspection challenging. Tiny defects, like microscopic cracks invisible to the naked eye, required specialized equipment. The lack of detailed defect data also hindered analysis and improvement.
Our client was looking for an AI-based visual inspection solution that would increase efficiency, reduce costs and deliver flawless products.
How we solved the problem /
Solution /
Our customized solution combined high-resolution cameras, macro lenses, AI and robotics. We started automated control in the press shop, where early defect detection is most economically advantageous.
Due to microscopic defects, some as small as 10 μm, we used a high-resolution camera and a macro lens. Motorized platforms moved products under the camera and captured multiple overlapping images, which the software combined into one comprehensive insight.
The system's core is image analysis based on AI deep learning, identifying product defects across the extensive product portfolio. A clear user interface lets operators mark and classify results and provide feedback for continuous learning.
The inspection station communicates with the robotic arm handling products within the press. A data management model generates detailed reports and statistics, allowing operators to track defect trends over time.
Used technologies /
Technologies /
The solution combines high-resolution cameras, macro lenses, motorized platforms, AI deep learning, robotics, an operator interface, continuous-learning feedback, and detailed quality-data reporting.
Direct outcome /
RESULT /
This case demonstrates the transformative power of AI in achieving quality excellence and production efficiency.
- Greater Efficiency: Inspection frequency increased from 1–5% to 20%.
- Improved Accuracy: 98% defect detection success rate with continuous learning.
- Reduced Costs: Prevention of defective pieces progressing through production.
- Data-driven Insights: Proactive measures to optimize production.
- Enhanced Customer Experience: Consistently high-quality and reliable products.
- Industry Impact: A benchmark for AI adoption in metalworking.
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