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This article discusses the implementation of artificial intelligence (AI) in printed circuit board (PCB) design. AI technologies, such as machine learning and deep learning, can be used to improve operational productivity and user expertise in PCB design. AI can automate manual tasks, accelerate decision-making, and optimize the performance of electronic systems. Specific areas where AI can be applied include component selection, component model creation, schematic connectivity, dynamic reuse, constraints, layout, analysis and verification, and design synthesis. By incorporating AI capabilities, PCB design processes can be streamlined, leading to cost reduction, shorter development time, and improved product quality. [Extracted from the article]

The technical evolution that continues through 2015 and beyond has been coming for a time, but only in the past few years have studies identified three key indicators driving that [...]

Deals with design methodologies that can shorten time-to-market and cut cost in the electronics industry. Details on the team design process of Philips Electronics; Focus of the company's process improvement; Function of printed-circuit layouts.

The article offers tips on managing impedance and minimizing insertion loss when laying out a high-speed printed circuit board. According to the author, insertion loss can be managed by using low-loss dielectric materials in the stack-up or by moving components closer to shorten traces. He states that another method is to widen traces to reduce skin effects. To manage impedance, he recommends stitching vias to shield signals from crosstalk produced by neighboring vias and to isolate signals.