Ensemble Machine Learning
A major aircraft manufacturer needed a fast way to identify critical stress zones from 3D computer models of new aircraft designs to optimise and reduce development time.
Arion proposed a predictive data model to quickly identify the critical zones prior to full Finite Element Analysis (FEM). We provided the data science leadership and advised on toolset selection to implement an advanced ensemble machine learning model.
The model was able to identify the critical zones for in-depth localized stress analysis. Typically, the model identifies these zones within minutes; traditional engineering FEM tool sets take more than a month of hands-on engineering effort.