How data-driven machine learning and autonomous process control enable end-to-end production in Additive Manufacturing

It is by now well understood that for Additive Manufacturing to mature, it needs to be faster, simpler, and more reliable. This presentation - the result of tight cooperation between Oqton and Baker Hughes - will highlight a step toward this goal through the development of an end-to-end AM workflow for the serial production of a Variable Resistance Trim (VRT) component. Built on a fully digital framework, it includes simulation, real-time process monitoring based on AI, anomaly analysis, and data preparation automation. It is a strong corner stone for an AM workflow that delivers consistent quality and the documentation necessary for certification.

Presentation language: ENG