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The New Chapter: Artificial Intelligence in PCB Design

With the rapid advancements in modern technology, a new era of PCB design is emerging, which includes the use of artificial intelligence (AI) and machine learning (ML). AI and ML have been all the rage in the news as they are becoming indispensable tools across various industries. Integrating AI and ML into the PCB design process not only elevates workflows and processes but also enhances the reliability and performance of products developed by the electronics industry.

For decades now, PCB designers could be seen spending countless hours grueling over the meticulous and time-consuming process of designing the latest PCBs. Often, the design could involve multiple iterations to achieve a product's desired performance and functionality. However, with new advancements in AI and ML, the PCB design landscape is being completely transformed by automating several aspects of the design process. AI algorithms can analyze large amounts of data from previous designs and apply previously taken information to developing projects. AI algorithms can suggest optimal layout designs, component placements, and routing paths. Using these algorithms not only speeds up the design process two-fold but also reduces the likelihood of significant errors. Reducing the likelihood of errors that may be common in modern PCB design today can result in more reliable PCBs in the future.

Component placement and electrical connection routing are some of the most critical challenges PCB designers have to face when designing modern PCBs. These tasks require careful consideration of various internal and external factors, which include thermal management, electromagnetic interference, and signal integrity concerns. Evaluating these factors from a designer perspective can take a significant portion of the designer’s time and energy. But with new AI-driven tools, these factors can be evaluated in real-time, while providing designers optimal suggestions for routing and component placement. With ML’s ability to learn from each design iteration, continuous improvement and time savings are inevitable. ML algorithms are helping designers now achieve more effective and efficient layouts.

An important task for the PCB designer is analyzing the reliability of their PCB in the making. As well as component placement and routing, AI and ML are playing a crucial role in elevating the reliability of PCBs. Machine learning is leading the way in predictive reliability analysis to identify potential pressure points of failure in a PCB design. ML does this by analyzing previously taken data from past projects and incorporating the environment of the PCB being used in a real-world setting. By using this setting, designers can address potential issues before the product is released into production, which significantly reduces the risk of failures occurring in the system in the future. Artificial intelligence, on the other hand, simulates a real-world environment through stress scenarios and various operating conditions. AI simulations like these can provide insights into how the PCB will perform under different load conditions.

One of the most critical aspects of PCB design, which usually occurs through the design process, are the design rule checks (DRCs), which are essential when ensuring that a design will meet manufacturing tolerances and standards. For decades, these checks have been typically performed manually, which makes them more prone to error and can be a significantly time-consuming process. With the help of AI-driven algorithms, DRCs are becoming a quicker and much simpler process. AI algorithms can automate DRCs, unlike the manually performed previous DRCs, which help to quickly identify potential DRC violations. AI is not only helping to identify the DRC violations, but also suggesting potential corrections to make to fix these violations. Through these algorithms, the design process is speeding up, and the reliability and accuracy of final products are enhanced.

Integrating AI and ML into current PCB design improves previous processes and designs and makes way for new product development and innovation. With AI and ML, designers can explore new materials through simulations, create novel design architectures, and create complex layouts with ease. AI allows for the integration of advanced device features inside simulations, which pushes the boundaries of modern PCB design.

Like any other modern technology, AI and ML are growing and evolving. Their role is expected to expand and develop in the PCB design industry. Advances in AI would include complex predictive modeling, fully autonomous design systems, and enhanced collaboration tools. These advances could enable the creation of more complex PCBs with minimal intervention. Integrating AI and ML in modern designs could redefine the future of not just the PCB design space but the entire industry.

Conclusion

AI and ML are completely changing how designers view their capabilities in the design space. These technologies are revolutionizing the PCB design industry by elevating reliability, enhancing efficiency, and optimizing design layouts. Through AI and ML, designers are becoming empowered to push the boundaries of PCB innovation, while also creating sophisticated and reliable electronic products. The future of artificial intelligence and machine learning is vast as these technologies are rapidly growing and creating continuous progress in the PCB industry.

Resources

• “AI & ML Optimization in PCB Design: Streamlining Processes,” Medium.com, April 21, 2024.
• ·“The Current State of AI in PCB Design in 2023,” by Zachariah Peterson, Altium.com, June 10, 2023.
• “5 Ways AI Will Revolutionize Hardware Design in 2024,” by Mattias Wagner, Built-in.com, March 12, 2024.

This column originally appeared in the June 2024 issue of Design007 Magazine.