The FERA I subproject is developing an innovative solution for repairing tools in the automotive industry: a semi-automated process chain that combines modern reverse engineering (3D scanning, CAD processing) with additive manufacturing (laser metal deposition, LMD). The aim is to repair and adapt defective tools precisely and efficiently, minimize manual steps, and increase process reliability.
The project is divided into three main work packages (WPs):
WP1: Automated repair of tools for the automotive industry
- WP1.1 (Data processing): Here, an automated process is being developed to create a 3D difference volume for repair from scanned tools. The user simply selects the relevant area and the software automatically generates the required data in STEP format.
- WP1.2 (LMD repair/adjustment process): In this step, an LMD process strategy is developed to reliably fill the previously created difference volume. Parameter studies are carried out and tool path strategies are investigated to define a safe processing window and ensure metallurgical quality.
- WP1.3 (Integration and testing): The results from WP1.1 and WP1.2 are integrated and the entire repair process is tested. A semi-industrial demonstrator geometry is used to test and validate the process chain on a real object.
WP2: Immersion and training at Fraunhofer IPK
This work package offers a five-day intensive training course in Berlin. Participants gain comprehensive insights into the entire process chain of additive manufacturing in toolmaking, including LMD repair, reverse engineering, and smart condition monitoring. Live demonstrations and company visits promote knowledge transfer to Brazilian application partners.
WP3: International market and technology analysis
The goal is a detailed market study on additive manufacturing in the tool, die, and mold making industry. Best practices, success factors, current hurdles, market figures, and future forecasts will be analyzed in order to provide strategic recommendations for the implementation of AM technologies.