This September, we're focusing on the impacts 3D printing is having on the Industry 4.0 ecosystem. MIT shares the perfect example of how additive manufacturing is elevated with machine learning that can monitor and adjust 3D printed parts to correct errors in real-time.
Scientists and engineers are constantly developing new materials with unique properties that can be used for 3D printing, but figuring out how to print with these materials can be a complex, costly conundrum.
Often, an expert operator must use manual trial-and-error — possibly making thousands of prints — to determine ideal parameters that consistently print a new material effectively. These parameters include printing speed and how much material the printer deposits.
MIT researchers have now used artificial intelligence to streamline this procedure. They developed a machine-learning system that uses computer vision to watch the manufacturing process and then correct errors in how it handles the material in real-time.