Laser-based metal powder bed fusion (AM) technology has now become the core technology for producing complex metal parts. However, traditional laser beam profiles and insufficient process monitoring often cause issues during the melting process, which can lead to material defects and production halts. This results in waste, increased energy consumption, higher production costs, and slower production workflows.
The EU InShaPe project, implemented by the Technical University of Munich in collaboration with nine other partners from France, Germany, Israel, Italy, the Netherlands, Sweden, and Spain, has developed a new approach combining AI-based beam shaping and multi-spectral imaging to address these challenges.
The research results significantly improved the production efficiency of powder bed laser 3D printing processes. In a series of industrial applications, they achieved a production rate increase of over 600% (6.2x), including a production speed of up to 93.3 cm³/h for high-temperature alloy components, compared to the initial production efficiency of only 15 cm³/hour. Meanwhile, the collaborative partners also reduced costs by 50%, achieving important project goals.
The project partners demonstrated the innovative technology of beam shaping and multi-spectral imaging (MSI) in five industrial applications: aerospace turbine blades (In718), industrial gas turbine components (In718), space combustion chamber parts (copper alloy), chainsaw motor cylinder heads (AlSi10Mg), and space communication satellite antenna components.
The combination of AI-based beam shaping and multi-spectral imaging technology has significantly improved the 3D printing process. The laser beam profile is specifically adjusted for each component, taking into account its unique geometry and materials. This enhances the quality of the parts, accelerates the processing speed, and prevents issues such as cracking, spattering, and condensation, which could otherwise lead to rework and waste.
The researchers of InShaPe found that combining a circular beam profile with an optimized scanning strategy is particularly suitable for various applications. Instead of using a Gaussian beam, they modulated the beam to distribute the intensity in a circular profile, thereby creating a stable melt pool. This results in a more stable melting zone and more uniform material processing.
At the same time, the new multispectral imaging system can capture signals from different wavelength ranges, allowing real-time monitoring of the printing process. This enables early detection of thermal changes in the melt pool. The recorded data is directly integrated into process management. Defects that previously caused production stoppages or required rework can now be avoided, allowing the production process to continue without major delays.
The industrial gas turbine components (material: IN718) in the energy sector were the first to be introduced into industrial-scale batch production. Overall, this innovative approach marks an important step forward in achieving industrial-scale production using powder bed laser 3D printing. The combination of smart beam shaping and MSI process control makes the melt pool more stable, reduces defect sources, and ensures the targeted use of less energy. As a result, the production speed of complex metal parts is faster, costs are lower, sustainability is enhanced, and quality is improved, significantly boosting production efficiency. InShaPe provides a valuable reference for the industrial sector to adopt AI-based beam shaping and MSI process control more quickly, advancing 3D printing technology and benefiting application industries such as aerospace, energy, and automotive.
