Dico
Assembly Line
Enhancing 3D Printing Defect Detection With AI Module
A team of South Korean researchers has developed an AI-enabled module designed to improve defect detection and optimization in metal 3D printing. This innovative module, which functions as an add-on component, can be integrated with existing factory equipment to autonomously identify defects and optimize production conditions without requiring expensive hardware upgrades. The research, led by Yoo Se-hoon and Lee Ho-jin from the Korea Institute of Industrial Technology, focuses on transforming traditional manufacturing setups into AI-powered smart factories. Their technology, called “Metal 3D Printing Defect Detection and Active Control Technology,” monitors production processes in real time and adjusts settings automatically, making it suitable for industries using older equipment. The AI module has been tested with Direct Energy Deposition (DED) 3D printing, a method where a high-energy laser melts and deposits metal powder or wire layer by layer. DED systems are prone to defects caused by variations in laser output, stacking speed, and powder supply. The module detects anomalies during the printing process, alerts operators, and actively adjusts parameters to maintain optimal conditions. Unlike traditional systems that rely on operator experience for troubleshooting, this smart module autonomously identifies and resolves errors, reducing downtime and enhancing production efficiency.