Affiliation:
1. AI in Manufacturing for Aerospace Engineering, TU Delft, 2628 CD Delft, The Netherlands
Abstract
This paper provides a detailed review of a digital thread for composite aerospace components. The current state of the digital thread continues to progress and at an ever-accelerating rate due to advancements in supporting technologies such as AI, data capture/processing/storage, sensors, simulation, and blockchain. While the individual steps that make up the digital thread have made manufacturing innovation and benefits possible, the connection points of the thread are not consistently solid, with many experiments and proof-of-concepts being conducted, but with few full digital threads in deployment. Key gaps include the ability to handle such large and continuous amounts of data, the infrastructure needed to capture and process them for insight, and the AI-based analytics to build and scale enough to obtain the expected exponential benefits for life cycle insight and manufacturing optimization. Though some of these gaps may take specific technology innovations to advance, there is a specific roadmap that can be deployed immediately in order to obtain “rolling ROI” benefits that will scale in value as this cycle is repeated across the product line.
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