When automotive manufacturers and suppliers apply artificial intelligence (AI) and machine learning (ML) to their full potential, it promises to multiply human capacity and accelerate the development and discovery of new technologies.
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!
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.
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:
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:
Watch the webinar to learn how to drive performance engineering using artificial intelligence.