Lawrence Livermore’s AI Vision System Catches Direct Ink Writing Defects Mid-Print

Direct ink writing is one of those 3D printing technologies that has a process that can vary significantly. It’s not very commercialized, and mostly reserved for research labs.

Now, a team of scientists and engineers at Lawrence Livermore National Laboratory (LLNL) in California have developed a camera-based inspection system that can monitor complex 3D-printed structures using AI and machine learning to measure small variations and potentially identify problems before a part leaves the printer. Described in npj Advanced Manufacturing, the system pairs printer-mounted cameras with machine learning and computer vision to turn thousands of in-print images into measurements and spatial maps of the deposited material.

Catching Problems Earlier

Direct ink writing can produce flexible cushions and pads that depend on strands only a fraction of a millimeter thick. Gaps, breaks or diameter changes can hurt performance.