• Project title: AI-supported, in-line measurement methods for determining the quality of metallic components and more efficient hardening processes (orig. title" KI-gestützte, In-line-Messmethoden zur Qualitätsbestimmung metallischer Bauteile und effizientere Härtungsprozesse")
• Acronym: IQMet
• Duration: 36 months (Start: 01.02.2025)
• Funding: FFG - Austrian research promotion agency
• Program: AI-Region Upper Austria

 

The aim of the IQMet project is to develop an inline-capable measurement method for the non-destructive determination of the surface hardness depth.

The main focus is on AI-based evaluation algorithms to extend the information content of the measurement data beyond classical signal processing. With the help of industrial image analysis and segmentation, advanced methods for machine learning and data analysis are used, which are applied in industrial practice.

The use cases include resource-saving production by reducing scrap during the state-of-the-art destructive testing of surface hardness depth. Furthermore, a simple and time-saving alternative to the existing test method.

RECENDT is developing and improving laser-ultrasonic methods for the non-destructive analysis of material parameters such as the surface hardness depth and the microstructure in induction-hardened components.