An overview: Strategies, tips and examples of how CADFEM AI can be used to improve products and development processes.
Arrange a consultationAI in product development
What does AI achieve in product development? How does it contribute to better products and processes? There are countless possibilities and immense potential.
Advantages of AI at product level
- Higher performance: By identifying and correcting errors and by uncovering additional potential, AI enhances product fault tolerance and performance.
- Maximum precision: The analysis of large amounts of data and the recognition of patterns by AI helps to ensure that future products meet the specified requirements with pinpoint accuracy.
- Optimal designs: AI-driven optimization techniques show how product designs can be systematically improved because they are strictly parameter-based.
- More innovation: AI algorithms support the identification and fast verification of new ideas. Information obtained will be reutilized.
Advantages of AI at process level
- Decision support: The precise predictions and real-time analyses of AI facilitate decision-making on key development issues.
- Speed: AI shortens iteration loops in the development process and creates additional scope for changes and improvements.
- Cost savings: The automation and optimization of tasks and processes through AI reduces costs.
- Knowledge base: AI facilitates the archiving, evaluation and provision of knowledge from various sources.
Examples
Simulation of various crash scenarios
Only 20 training data and 4 for testing
| Prediction time | Accuracy |
| 17,5 s with CPU | R2 0,956 |
Simulation of a drohne Antenna position
Only 37 training data and 4 for testing
| Prediction time | Accuracy |
| 10s with CPU | R2 0.969 |
Cooling Simulation of an Electric Motor
Only 21 training data and 2 for testing
| Prediction time | Accuracy |
| 12s with CPU | R2 0.964 |
Josef A. Overberg
Managing Director CADFEM Germany GmbH, in an expert survey by the trade journal “Industrielle Automation” (Vereinigte Fachverlage, 03-2024)The basis is important for all AI approaches - digitalization. In product development, it is high and the path to efficient use is not far - if a company has done its homework. This means understanding simulation and data collection as integral components of an end-to-end digital engineering process and creating the corresponding workflows and infrastructures. This is exactly what we see with our customers, who are already successfully using AI and receiving the required answers in real time with the AI-supported optimization of their products or AI-based digital twins.
The right solution for you
With CADFEM AI, we accompany you competently with tools and services on your way into the world of artificial intelligence.
What can we do for you? We look forward to talking to you.
