Wed, Oct 26, 2022 2:00 AM - 3:00 AM CST
Improving design and
manufacturing processes in aerospace and defense requires understanding and
accounting for uncertainties. For example, there will be uncertainty in the
properties of the materials used and manufacturing process for any component.
Even for a perfect process that produced identical components, each may be
deployed in different conditions. Determining optimal design configurations or
manufacturing processes under such uncertainties is difficult and can require
substantial time using physical experiments and physics-based simulations (e.g.
CFD and FEA). Also, it is time consuming to sort through large amounts of
manufacturing data in order to identify the most useful and relevant
information. The solution is to first train an AI or machine learning model
using data from the design or manufacturing process collected by an intelligent
sampling plan. Once trained, the model can rapidly make accurate predictions
for all what-if scenarios. With the roadblock of computational cost removed,
many otherwise infeasible analyses may be conducted to improve the design or
process. Join us for this webinar to learn how AI and machine learning models
can be used to enhance aerospace and defense design and manufacturing
applications.