Acceleration of development through AI and physical models
The development of products and processes can be cost- and time-intensive. Artificial intelligence and physical models can contribute to simplify and accelerate development. In this blog, we will show you two application scenarios.
Aircraft wings should not only provide the aircraft with sufficient lift and stability, but at the same time be designed to minimize air resistance. The development resembles an aerodynamic marvel that can only be achieved by using vast amounts of data. Artificial intelligence and physical models can make the development process faster and more efficient. With the help of physical simulations, the optimal shape of aircraft wings can be predicted.
In this blog, we will show you in which two scenarios the combination of artificial intelligence and physical models is used and how this opens new optimization potential:
For production planning, the interaction of AI and physical models can be the decisive added value for companies. The optimal utilization of production lines and their units is a complex process that can be simplified by artificial intelligence. Production planning is simulated and set up on a daily basis based on different situations. In this way, a high number of variants, such as in a paint shop in automotive production, can also be covered and planned accordingly thanks to AI.
In the field of predictive maintenance, critical components can be monitored with the help of artificial intelligence and Machine Learning. Sensors detect the smallest damage to the components and can filter them out at an early stage. Thanks to AI and ML, noise due to environmental influences can be excluded if they are fed with physical algorithms.
AI/ML models open completely new practical options for application that can be used in a wide variety of processes.
In the second part of our article “New optimization potentials thanks to AI and physical models”, we will explain which other application scenarios are possible with AI/ML and physical models.
Latest posts by Marc Tesch (see all)