In product development, CAE models are widely used to predict product performance. However, conventional CAE models had issues such as enormous calculation times and the need for advanced skills in model creation.
To address this, Athens Brainy proposes the construction of surrogate models using AI technology. A surrogate model is a model for accurately predicting output results from input conditions without performing high-load physical simulations. This significantly relaxes the temporal and technical constraints of CAE, realizing efficiency and acceleration in product development.
While utilizing the results obtained from initial CAE models, we iteratively perform data collection, feature engineering, and model selection steps to gradually improve the prediction accuracy of the surrogate model. Eventually, it becomes possible to predict performance at a dramatically faster rate while maintaining accuracy equivalent to CAE.
By combining Athens Brainy's AI technology with CAE expertise, we innovatively solve product development challenges that were previously difficult.