Issue link: https://iconnect007.uberflip.com/i/1522071
50 DESIGN007 MAGAZINE I JUNE 2024 algorithms not only speeds up the design pro- cess 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 con- nection routing are some of the most critical challenges PCB designers have to face when designing modern PCBs. ese tasks require careful consideration of various internal and external factors, which include thermal man- agement, 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 A I - d r i v e n to o l s , these factor s can b e e v a l u a t e d i n real-time, while providing designers optimal sugges- tions for routing and compo- nent placement. With ML's abilit y to learn from each d e s i g n i t e r a t i o n , c o n t i n u o u s i m p r o v e m e n t a n d t i m e s a v i n g s a r e inevitable. ML algorithms are helping design- ers 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 reli- ability 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 pro- vide 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 pro- cess, 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 auto- mate DRCs, unlike the manu- ally performed previous DRCs, which help to quickly identify potential DRC vio- lations. AI is not only help- ing to identify the DRC violations, but also suggesting potential corrections to make to fix these violations. rough 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, cre- ate novel design architectures, and create com- plex layouts with ease. AI allows for the integra- tion of advanced device features inside simula- tions, which pushes the boundaries of modern PCB design. Like any other modern technology, AI and ML are growing and evolving. eir role is expected to expand and develop in the PCB design industry. Advances in AI would include complex predictive modeling, fully autono- mous design systems, and enhanced collabo- ration tools. ese advances could enable the Like any other modern technology, AI and ML are growing and evolving.