According to the World Economic Forum Jobs of Tomorrow article, engineering skills are one of the highest-demand skills. Indeed, engineering has always been considered an evolving industry. The increase of AI technologies actually enable engineers to complete their work more efficiently and solve a wider range of problems, empowering their own expertise, and making them the main actors of future’s development and success.
From a practical perspective, how are these tools integrated in the design process within the automotive and aerospace industries ?
The standard design process in industrial product development consists of regular interactions between CAD engineers/designers and the simulation teams. At different stages of the development process, with evolving requirements, new designs need to be assessed and improved using standard CAD/CAE tools. These interactions involve consequent waiting times and the simulation tools are not always compatible with the requirements of fast-paced engineering projects. Furthermore, different file formats and the complexity of tools used by the simulation teams are often further slowing down the process.
Quicker simulation approaches integrated in design tools is an attractive alternative. However, most of these tools lack accuracy, do not correlate well with the “high-fidelity” simulation and are limited to a few simplified scenarios proposed by the software vendors. These are bottlenecks that Neural Concept Shape is solving, with a new class of AI-based algorithms.
As Shape models are handling raw 3D CAD and CAE data, simulation can be frontloaded in the design process, providing designers a real-time and simplified access to simulation results. Designers can now, on their own, iterate on the design and provide the end customers with a faster and better solution. Indeed, all simulations are standardized and become available within their CAD interface. Designers can intuitively interact with fast and accurate simulations independently.
And what about the CAE teams?
They remain at the core of the design process. Using their knowledge and experience, CAE teams are now becoming responsible for the quality, update and deployment of these AI models. Their expertise empowers the designers with additional tools, which is a massive gain in competitiveness for the entire company.
This new workflow also means a much smarter usage of CAE tools. In conclusion, AI approaches will not replace simulation softwares nor engineers. AI will rather be used by simulation experts to validate concepts, or explore much more complex physical phenomena (such as aero-acoustic if we talk about a CFD application), while the early development process is done within the design teams.