A Federated, Multimodal Digital Thread Platform for Enabling Digital Twins

The "digital twin" is emerging as a dominant paradigm aimed at improving outcomes associated with physical counterparts within several industrial sectors. Recently, the paradigm has been gaining traction in design and engineering scenarios. Critical to the creation and maintenance of a digital twin is a "digital thread" that allows the continuous collection and linking of relevant data and analytical models throughout the lifecycle of a physical entity. This paper describes GE Research's digital thread approach, comprising a federated multimodal data platform integrating modern semantic and Big Data technologies. We demonstrate the value of our digital thread platform in enabling the digital twin of an additive manufacturing process and system to accelerate time-to-market of game-changing new parts for the aviation, power and healthcare industries.