Researchers enhance 3D printing defect detection with AI
The module automatically detects defects and finds the best production conditions
According to ChosunBiz, Korean researchers have created a 3D printing module that connects to existing factory equipment to use artificial intelligence (AI). The module automatically detects defects and finds the best production conditions. The research was led by Yoo Se-hoon and Lee Ho-jin, both senior researchers at the Korea Institute of Industrial Technology.
This system, called ‘Metal 3D printing defect detection and active control technology’, can be installed by attaching an ‘add-on’ module to older production equipment without AI. The add-on is made up of sensors, defect-detection features, and controls that make equipment smarter. By using this module, companies can turn their current factory setups into AI-driven smart factories without replacing their machinery.
The researchers tested the module with direct energy deposition (DED) 3D printing, where mistakes with laser output, speed, or powder supply can easily cause defects. The add-on notices any abnormalities during printing and shows alerts on a display. It also automatically adjusts settings to fix issues – reducing the time and expertise needed to find the right printing conditions. This makes it especially useful for manufacturers who don’t have specialized equipment or workers.
The researchers have already transferred this technology to Korean companies MR Tech and Dico for commercialization. “The technology detects various stacking defects using deep learning technology and actively controls the conditions of 3D printing equipment in real-time. It is expected to have a significant impact as it can also be applied to implement digital twin virtual models of production process data,” said senior researcher Lee Ho-jin.
“It can also be applied to robot-based production processes, and we are promoting the commercialization of AI-based robot 3D printing technology,” said Moon Chang-kyu, head of MR Tech.
“It has a high competitive advantage in terms of being able to obtain and manage temperature data of production processes based on video systems,” and continued, “We plan to apply it in aerospace, medical, and automotive fields,” said Hwang Jun-cheol, CEO of Dico.
