Insight. Implementation. Integration.

AI, or artificial intelligence, is transforming the products we build and the way we do business. It also presents new challenges for those who need to build AI into their systems. Creating an “AI-driven” system requires more than developing intelligent algorithms. It also requires:

• Insights from domain experts to generate the tests, models, and scenarios required to build confidence in the overall system
• Implementation details including data preparation, compute-platform selection, modeling and simulation, and automatic code generation
• Integration into the final engineered system

Jason Ghidella demonstrates how engineers and scientists are using MATLAB^® and Simulink^® to successfully design and incorporate AI into the next generation of smart, connected systems.

Lightyear One is a remarkable innovation: It is an all-wheel drive, five-seater electric car charged by the sun. The key challenge of this innovation is matching the energy required while driving, with the limited and fluctuating energy yield of the solar panels. MathWorks solutions are used by Lightyear engineers as the “Swiss Army knife” to address this challenge, optimizing the energy flow from the solar panel and its accompanying electronics to the vehicle. This presentation provides an overview of Lightyear’s accomplishments to date, and its ongoing mission: clean mobility for everyone.

Atlas Copco is constantly looking for ways to improve their products and services throughout the whole product lifecycle of their machines in all aspects.  To reduce cost of ownership, they integrate simulation and data analytics from engineering to production, sales, and services. One of their objectives is to enable thousands of sales engineers to do reliable performance simulations during customer engagements while interacting with customers. Another objective is to allow the services division to set up different customer-specific maintenance strategies based on real-time data collection from more than 100,000 machines in the field.

Connecting colleagues, customers, and the supply chain using a single source of truth results in shorter manufacturing throughput times and improved workplace safety. This is achieved by establishing an enterprise-wide data acquisition and analytics platform. The importance of a model-based engineering approach is key.

This presentation will showcase how this approach leads to better products and services throughout the whole product lifecycle.