Reducing Electronic Systems Design Complexity with AI

Imagine what it would be like if your electronic system design tools had AI, ML, and DL technologies built in. This is the Siemens vision: incorporate AI, ML, and DL algorithms into products to accelerate design creation and reduce process complexity. This paper explores crucial electronic systems design areas where artificial intelligence (AI) technologies — including machine learning and deep learning — can be applied to minimize or eliminate the complexity of electronic system design work.

Challenges in PCB Design in the Application of AI

PCB electronic systems engineers are challenged to generate designs that have adequate power and cooling for complex, fast ICs while maintaining signal and thermal integrity for every high-speed signal between the various ICs on a board. Designers must deliver these more complex PCBs and interconnected electronic systems with best-in-class performance at the lowest power possible — and do so within shrinking time-to-market windows. This whitepaper describes several of the key challenges faced by PCB designers and engineers in realizing this goal and how AI could address them.

Siemens’ goal is to deliver AI enhanced tools that help electrical engineers and designers:

• Make informed decisions, increasing efficiency

• Complete routine tasks with minimal effort, improving productivity

• Improve expertise by recommending next tasks

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