video

Leverage artificial intelligence and machine learning in automotive engineering

Artificial intelligence helps improve design processes, increase accuracy, and speed up product development in the automotive industry. But where should you start?

This video explores embedded artificial intelligence technology and machine learning in the Siemens Simcenter solutions. Our digital software solution helps engineers take advantage of artificial intelligence potential in all stages of vehicle development to support engineering better vehicles faster — Watch now to learn more.

Engineer better vehicles, faster with artificial intelligence

Today, engineering departments must develop innovative products that integrate mechanical functions with electronics and controls, utilize new materials and manufacturing methods, and deliver new designs within shorter design cycles. Artificial intelligence (AI) technologies enable automotive engineers to do better with more significant insights and a broader reach. By combining physics-based simulations with insights gained from data analytics, Siemens Simcenter helps engineers optimize the design and deliver innovations faster and with greater confidence.

Speed up simulation while ensuring accurate results with AI and machine learning

AI-based learning controls help optimize control strategies for superior operational performances. Combined with simulation, AI can generate virtual sensors that efficiently manage the complexity of controls. And while AI is pervasive in autonomous vehicle development, it proves particularly helpful in training machine learning models to display human-like behavior when driving in complex traffic situations. No matter at which stage of development, AI and machine learning allows engineers to speed up simulation while ensuring accurate results and evaluate more alternatives faster with less processing time.

Use AI to produce stronger, more durable products

Embedding AI in the workflow helps engineers focus on the relevant architectures that meet the engineering objective. In materials engineering, AI brings a paradigm shift by supporting the creation of design-driven materials that adjust to product engineering goals. By adding smart data where it’s missing, AI can help ensure the structural integrity and the fatigue performance of 3D printed components. As a result, AI helps deliver more robust and durable products.

Discover artificial intelligence and machine learning solutions that can enhance your engineering development process to deliver better vehicles faster — Watch the video now!

Share

Related resources

Adapt to the future of energy with cloud-native design
E-book

Adapt to the future of energy with cloud-native design

Design complex electrical systems 5x faster with a cloud-native electrical CAD software for SMBs. Learn more.

The advantages of Cloud-Native Electrical Cad for Industrial Applications
Webinar

The advantages of Cloud-Native Electrical Cad for Industrial Applications

The field of electrical computer-aided design (CAD) is undergoing a transformation like never before. Traditional CAD software is making way for a new paradigm – Cloud-Native Electrical CAD.

New cloud-native Capital X Panel Designer electrical design SaaS offering helps small to medium sized businesses
Blog Post

New cloud-native Capital X Panel Designer electrical design SaaS offering helps small to medium sized businesses

Siemens Capital X Panel Designer gives individual electrical designers or small teams an affordable yet powerful electrical design solution Siemens…