In this white paper, discover a framework for applying AI to the vehicle development process. Illustrated with examples, it identifies specific scenarios where the machine can complement the human mind to achieve speed and efficiency and turn the increasingly complex world of today's engineering into an advantage — Download the full white paper now!
Use machine learning to complement the human mind in vehicle design
Now is the perfect time to take advantage of AI, as the two critical enablers have become prevalent in the automotive engineering space: big data and processing power. Simcenter can help you take advantage of the potential of artificial intelligence in all stages of the engineering development process and support you in enhancing processes and engineering better vehicles faster.
Benefits of deploying AI in the vehicle design process:
Get a head start in subsequent designs by leveraging historical data
Catch mistakes that will likely go unnoticed until it is too late
Speed up the analysis and process data faster
Optimize your design with confidence
Accelerate product development with the 3Ds framework for applying AI
Simcenter provides a practical framework for applying AI and ML: dull, data-rich, and decision support identifies specific scenarios where the machine can complement the human mind to achieve speed and efficiency that is higher than today.
Dull activities: Automate repetitive and tedious work to reduce expensive labor wasted on unskilled tasks.
Data-rich environments: Leverage supervised and unsupervised learning methods to extract insights from large datasets generated from CAE and testing.
Decision-support: Eliminate subjective decision-making and uncover anomalies in a design before the product fails using AI algorithms.
Use AI to create accurate subsystem models of complex nonlinear systems
AI and ML can create accurate subsystem models of complex nonlinear systems in a fraction of the time without having to model the physics and fine-tune the model. Automotive manufacturers and suppliers can better use this data to recognize trends and make smarter decisions with:
Target setting and benchmarking