Algorithm learns to correct 3D printing errors for different parts, materials and systems

Example image of the 3D printer nozzle used by the machine learning algorithm to detect and correct errors in real time. Engineers from the University of Cambridge have developed a machine learning algorithm that can detect and correct a wide variety of different errors in real time, and can be easily added to new or existing machines to enhance their capabilities. Details of their low-cost approach are reported in the journal Nature Communications. However, it is also vulnerable to production errors, from small-scale inaccuracies and mechanical weaknesses through to total build failures. Currently, the way to prevent or correct these errors is for a skilled worker to observe the process.