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Research & Development

Research project aims to optimize 3D-printed parts for laser welding

01 Jun 2021

“QualLa” project is partnership of LZH and Institute for Integrated Production, both based in Hannover, Germany.

Effectively welding 3D-printed components by laser is the goal of a partnership of scientists working at the Institute for Integrated Production Hannover and Laser Zentrum Hannover.

In their new research project QualLa (“Quality assurance in laser welding of additively manufactured thermoplastic components”), they are working to develop an expert system to support small and medium-sized enterprises in optimizing additive manufacturing processes – so that the printed components can subsequently be welded securely with the laser.

For injection-molded plastic components, laser transmission welding is already an established industrial joining process. For components from the 3D printer, however, such joining does not yet work because cavities and boundary layers in the 3D-printed components prevent a uniform weld.

These features are individual to each component because, in additive manufacturing, no two components are alike. Even components from the same series are only identical on the outside; the internal structure can be different, say the partners.

Expert system

To enable small and medium-sized enterprises to weld 3D-printed plastic components with lasers without analyzing each component in detail in advance, the IPH and LZH scientists want to develop an expert system and bundle process knowledge in the associated computer program.

In project QualLa, the researchers are looking at fused deposition modeling (FDM) for this purpose. In this additive process, thin strands of molten plastic are superimposed, layer by layer.

Even before the 3D printing process starts, the expert system is intended to provide recommendations on which material, which layer thickness, and which layer orientation are best suited to achieve the highest possible transmission – in other words, the highest possible permeability for the laser beam.

AI adaptation

In addition, the scientists want to develop a method to measure the transmission with spatial resolution. This involves determining for an individual component at which points the laser beam is transmitted and to what extent. This data will then be used to control the laser transmission welding process with the help of the expert system.

If the laser beam is transmitted less at a certain point, then the laser power must be increased. If the component is more light-transmissive at another point, lower laser power is enough. The researchers' goal is to develop a process control system that adjusts the laser power as a function of transmission so that a uniform weld seam is produced – even if the 3D-printed component does not transmit the laser beam uniformly.

The scientists want to use machine learning methods to process the information. The plan is to use neural networks, a type of artificial intelligence that makes the expert system capable of learning. The system will learn to recognize correlations between various input variables and the print result independently and thus predict the expected transmission.

Joining plastics by laser

Laser transmission welding can be used to join components made of thermoplastics – contact-free, automatable, without mechanical, and with low thermal stress. Two joining partners – one made of transparent, one of non-transparent plastic – are welded to each other with a laser beam.

The laser beam penetrates the transparent joining partner, and as soon as it hits the non-transparent plastic, the laser light is absorbed and converted into thermal energy. As a result, the plastic in the joining area melts, and a weld seam is created.

IPH and LZH are working closely with the industry on the research project. The committee accompanying the project includes companies from the fields of laser technology, additive manufacturing and plant engineering. Other companies are wel-come to participate in the project – companies involved in artificial intelligence or additive manufacturing are particularly sought after.

TechnoTeam Bildverarbeitung GmbHLightPath Technologiesart Photonics GmbHJENOPTIK Light & OpticsLASEROPTIK GmbHTechnoTeam Vision USA Inc.SPECTROGON AB
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