Speaking to ChatGPT about AI PCB design, and AI circuit design

A Chat with ChatGPT About AI PCB Design

Is AI PCB design one achievable route away or is there more to it?

Artificial intelligence has been on everyone’s lips since newspapers, radio, television, and social media have been overflowing with reports on the AI-based text generator ChatGPT since the beginning of the year. In fact, the text results delivered by ChatGPT are quite amazing, and many people – including the author of these lines – have for the first time realised that AI is not just a complicated “academic fad”, but in fact, much farther advanced than many of us could have imagined in their wildest dreams.

A Chat with ChatGPT

We do not however intend to indulge at this point in speculations about the effects of AI-based content generation on intellectual property, but rather would like to know if artificial intelligence is able to assist the complex task of laying out modern electronic assemblies in the near future. We, therefore, decided to have a chat with ChatGPT itself to find out from artificial intelligence itself what we can expect to see in this area.

Preempting the details, there are indeed a number of possible usages of AI that can help to complete routine tasks such as AI PCB design optimisation for more efficient, error-free PCBs, and quite possibly further down the line, push the boundaries of physics. However, the technology is still in the early stages of development, with progress to be made in the area of data acquisition (building up a database of reference designs) and in capturing the increasingly complex design rules that need to be observed in PCB design – and Zuken is on actively researching an implementing AI-based functionality in its PCB design environment, some of which are briefly touched at the end of the article.

How can AI help in PCB design?*

*Questions and answers of this “interview” are direct responses from ChatGPT

ChatGPT: Artificial Intelligence (AI) can help in Printed Circuit Board (PCB) design by automating tasks, increasing efficiency, reducing errors and enabling innovative design solutions. Some examples of AI-aided tasks in PCB design include:

  • Component placement optimization
  • Routing optimization and trace length reduction
  • Signal integrity analysis and prediction
  • Dynamic voltage drop analysis
  • DFM (Design for Manufacturability) checks
  • Design rule checking and violation correction
  • 3D visualization and interactive placement
  • Machine learning-based failure prediction and analysis.

By using AI, PCB designers can reduce design time, improve design quality and create innovative designs with increased functionality.

Speaking to ChatGPT about AI electronic circuit design and design data
A glimpse into the future: Zuken’s approach to AI in PCB design

Is AI Mature Enough to Efficiently Support PCB Designers Today?

ChatGPT: AI technology for supporting PCB design is still in its early stages of development and is not yet fully mature. While AI algorithms can perform certain tasks such as component placement optimization and design rule checking with good results, there are still limitations and challenges that need to be addressed. Some of these limitations include:

  • Limited understanding of complex design rules and constraints, leading to suboptimal results
  • Lack of data to train AI algorithms for new and specialized design tasks
  • Integration with existing design tools and workflows, leading to a fragmented design process
  • Limited ability to handle exceptions and unanticipated scenarios.

AI technology in the field of PCB design is rapidly advancing and has the potential to significantly impact the design process in the future.

Are you Aware That Zuken is Among the Forerunners in AI PCB design?

ChatGPT: Zuken is a company that provides software solutions for electronic design automation (EDA) and is involved in the area of AI-based PCB design. Zuken’s offering in this area includes a range of software tools and solutions designed to assist engineers in the design and verification of printed circuit boards (PCBs).

One of their offerings is the “CR-8000 Design Force,” a platform for advanced PCB design and system integration that utilizes AI and machine learning to automate design tasks and streamline the design process. The platform provides features such as automatic component placement, real-time design rule checking, and 3D visualization.

Zuken’s AI-based offerings in the area of PCB design are aimed at increasing efficiency and accuracy in the design process, reducing errors and design iterations, and improving overall design quality. The company’s focus on AI-based solutions reflects the growing trend towards the use of AI and machine learning in the EDA industry.

Are you Able to Make Predictions About the Future of AI PCB design?

ChatGPT: An error occurred. If this issue persists please contact us through our help center at help.openai.com.

Speaking to ChatGPT about the future of AI PCB design
AI operates on existing data – it is unable to make predictions of the future

We appreciate your insights into the opportunities of AI-assisted PCB design!

ChatGPT: You’re welcome! I’m glad I could provide some insights. If you have any further questions or need more information, feel free to ask. I’m here to help!

Since ChatGPT failed to provide an answer about the future of AI in PCB design…

… here are some of the areas in which Zuken is investing or already deploying AI technology:

  • New command recommendation: which AI suggests the next operational step based on the experts’ manipulation history AI learned
  • Circuit recognition and reproduction: AI recognizes circuits and components from acquired data and automatically reproduces the proven layout and routing.
  • Distancing: AI automatically adjusts the distancing between components or tracks and their relative positions of them.
  • AI-driven optimization of pin counts: AI delivers highly accurate results with
    a shorter time to design and less dependence on designers
  • DR optimization using AI: Based on DR check items used in past data, AI automatically extracts items that need to be checked in circuits and applies a check rule.

To learn more, come see us at ZIW!

See us at one of this year’s Zuken Innovation World Events to find out more about the state of the art in AI-based PCB design!

Kyle Miller, Technology R&D Manager at the Zuken Technical Center in Bristol UK will present the first results of AI-based auto-routing from Zuken’s AI development roadmap, now available for use in Release 2023 of CR-8000 Design Force.

ZIW Event Dates


Next Steps: On-Demand Webinar ‘AI-Based PCB Place and Route is All About Machine Learning’

This webinar will explore the current state of AI-based PCB design, its advantages, limitations, and the future. It will examine Zuken’s new Autonomous Intelligent Place and Route (AIPR) and how companies and users will benefit. You don’t want to miss this webinar if you are interested in AI-based design solutions.

On-Demand Webinar

Klaus Wiedemann
Klaus Wiedemann
Marketing Manager Europe
Klaus Wiedemann is responsible for Marketing Communications across Europe covering web content, public relations and marketing programs. He works with customers to highlight their success through case studies and presentations for Zuken Innovation World events. Klaus is an enthusiast for two-wheeled vehicles and owns several classic bikes he likes to maintain and repair.