By: Chris Rackauckas
Re-posted from: https://info.juliahub.com/blog/digital-echo-industrial-surrogate-modeling
Industrial surrogate modeling is typically centered around neural network architectures and precision. While important, these approaches don’t necessarily solve the ‘surrogates problem’. The ‘surrogates problem’ refers to the challenges associated with integrating surrogate models into industrial processes and requirements infrastructure. The challenge with this approach is that it doesn’t integrate surrogates into industrial processes and requirements infrastructure. For surrogate modeling to truly solve real-world industrial engineering problems, verification and validation benchmarks are equally important. This blog post looks at the three key pillars to create surrogates that are process-driven, reliable, and prioritize prediction time for varied industrial applications.
