Siemens Expands Simcenter with AI-driven Generative Engineering for Systems Architectures

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Siemens Digital Industries Software announces the release of Simcenter™ Studio software, a web application dedicated to discovering better system architectures, faster. Simcenter Studio offers a unique competitive advantage for designing products by finding the best possible system architectures in a shorter amount of time, searching through thousands of possibilities using artificial intelligence and system simulation. These results are automatically generated to meet the user’s design requirements and deliver specific systems architectures faster than ever before. This AI-based generation of system architectures is the latest addition to Simcenter™ software within Siemens‘ Xcelerator™ portfolio.

Today, engineers rely on individual expertise and known rules, and only evaluate a limited number of system architecture variants before choosing the “right” concept for time sensitive projects. Simcenter Studio allows organizations to overcome these hurdles by using AI-based techniques to vastly expand the design space and perform rapid evaluations of system concepts to identify the most promising designs earlier in the development program. This new generative engineering approach to architect complex systems has applications in various industries including automotive, aerospace and heavy machinery.

“The expansion of generative methods toward system architectures will provide a clear competitive advantage for companies that design complex systems,” said Peter Bilello, President and CEO, CIMdata. “With the introduction of this new offering, Siemens has demonstrated leadership by bringing together AI and system simulation for the conceptual stages of system design.”

The tight integration of system simulation inside computational notebooks in Simcenter Studio is unique to the market and is complemented with an automatic generation of controllers to enable realistic trade-studies. This allows for the evaluation of the most important key performance indicators (KPIs) to be reliable and properly facilitated when making business and engineering decisions.



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