Hard to believe that 3D printing has been with us for more than 40 years. Yet, additive manufacturing (AM), which can deliver enormous value, is still greatly underutilized. When properly implemented, the technology can reduce material waste and energy costs, improve part reliability, decrease lead times, reduce or eliminate the need to carry inventory and optimize the production of legacy parts.
However, transitioning to AM requires not only a change in mindset but more importantly, the ability to quickly and easily identify which parts are best suited for the additive manufacturing process. This is where AI and machine learning are now bridging the gap between traditional AM –where most of its value materializes in the form of functional prototypes – and more advanced additive manufacturing operations.