QATM QAI

QATM QAI

QAI is an AI-powered image evaluation solution integrated into Qpix Control2 software for automated hardness testing. Designed for Vickers, Knoop, and Brinell methods, it automatically detects and evaluates hardness test indentations with high accuracy—even on low-contrast, rough, or etched surfaces. QAI improves measurement consistency, increases automation, reduces manual intervention, and operates entirely offline to ensure data security and reliable, repeatable results.

QAI

AI-supported object recognition: faster, more accurate, more intelligent.

Discover the future of hardness testing with our groundbreaking AI integration, QAI. Our technology sets new standards in precision and efficiency by utilising cutting-edge AI models specifically designed for the challenges of Vickers, Knoop and Brinell hardness testing. The QATM quality standard and the ability to guarantee increased performance through retraining make QAI second to none in the industry.

Experience a level of automation never seen before: our AI automatically and accurately detects hardness test indentations – even on the most challenging surfaces. Say goodbye to manual intervention and hello to efficiency that paves the way for innovation. With our unrivalled accuracy and success rate, we offer you the ultimate competitive advantage. Revolutionise your hardness testing with our QAI – the future belongs to the pioneers!

Fully automatic indentation detection, even with low contrasts and difficult surfaces

This image evaluation is used in all areas of hardness testing, generally increasing the recognition rate, finding indentations in an image, and the quality and accuracy of the evaluation and analysis.

AI-based image evaluation significantly improves the quality of hardness test indentation detection.

Examples of surfaces with challenging conditions

The QAI offers greater added value for rough, grinded and etched surfaces. Especially with difficult material surfaces or etched surfaces, the recognition rate could be increased enormously.

Low contrast on steel material

  • Hardness: 725 HV1
  • Preparation: grinded P1200/polished 1µm

Low contrast on etched surface on steel material

  • Hardness: 309 HV0.5
  • Preparation: grinded P1200/polished 1µm

Low contrast on etched surface on carbon steel

  • Hardness: 121 HV1
  • Preparation: polished 1µm

Low contrast on etched surface on construction steel

  • Hardness: 235 HV0.5
  • Preparation: grinded P1200 / polished 1µm

Etched surface on steel material

  • Hardness: 305 HV0.5
  • Preparation: grinded P1200 / polished 1µm

Low contrast on etched surface on steel material

  • Hardness: 837 HV0.5
  • Preparation: grinded P1200 / polished 1µm

Big deformation/bulging on steel material

  • Hardness: 263 HV10
  • Preparation: polished 1µm

Small indentation on cast iron

  • Hardness: 361 HV0.01
  • Preparation: polished 1µm

Rough surface on steel material

  • Hardness: 287 HV10
  • Preparation: grinded P80

The use of QAI image recognition has also increased the repeatability and systematic deviation of the machine. The accuracy of the evaluation has a major influence on the relative repeatability of the machine.

Comparison between Classic evaluation and QAI evaluation

90 Hardness test points on a test block HV1 value 701 HV. The different evaluation modes are carried out on the same 90 indentations.

Classic Evaluation

Mean value Range
700,04 24,90
Hardness min. Hardness max.
688,80 713,70
Results OK
5,88 90