Leveraging DigitalClones for Prognostics Health Management

Use of physics-based models of aerospace components in the form of digital twins for prognostics health management offers impactful new opportunities to increase safety and reduce costs. As on- and off-board computational processing and storage capabilities continue to increase, leveraging these high-fidelity models becomes more and more appealing. However, challenges remain to implement these types of models in the aerospace domain, including availability and accessibility of the right data and validation of the underlying models. Fortunately, many of these challenges are being addressed through research in the aerospace industry and through implementation of digital twin technologies in adjacent industries, such as the wind energy industry.

Keywords: digital twin, prognostics, health management, physics-based model