Explainable AI for engineering design: A unified approach of systems engineering and component-based deep learning. (arXiv:2108.13836v2 [cs.LG] UPDATED)

Data-driven models created by machine learning gain in importance in all
fields of design and engineering. They have high potential to assists
decision-makers in creating novel artefacts with a better performance and
sustainability. However, limited generalization and the black-box nature of
these models induce limited explainability and reusability. These drawbacks
provide significant barriers retarding adoption in engineering design. To
overcome this situation, we propose a component-based approach to create
partial component models by machine learning (ML). This component-based
approach aligns …

ai arxiv deep learning design engineering explainable ai learning systems