Problem
Research questions and friction points this paper is trying to address.
Generative AI
PCB design
hardware automation
domain-specific data scarcity
tool integration
Surveying GenAI-based Automation in Printed Circuit Board Design and Test
🤖 AI Summary
This study addresses the lack of systematic research on generative artificial intelligence (GenAI) across the full lifecycle of printed circuit board (PCB) development by proposing the first GenAI application taxonomy tailored to the PCB domain. Spanning stages from supply chain management and specification definition to circuit design, layout optimization, verification testing, and assembly distribution, the framework is developed through a systematic literature review and taxonomic analysis. The work critically examines the applicability and limitations of GenAI in hardware design automation, identifying key challenges such as data scarcity and insufficient toolchain integration. Beyond highlighting the substantial potential of GenAI in PCB design and testing, this research establishes a clear technical roadmap to guide future investigations in the field.
📝 Abstract
Generative artificial intelligence (GenAI) is increasingly used for applications in the hardware and software domains. It purports to reduce the manual effort involved in the development and testing of complex systems before release. Within the hardware space, most tasks have focused on design automation of integrated circuits, particularly with hardware description languages. However, other types of hardware also exist! In this survey, we instead examine how GenAI has been and is being across the printed circuit board (PCB) design life cycle. This includes everything from supply chains, system specification, circuit design, layout and optimisation, validation and test, and PCB assembly and distribution. Through this lens we present a taxonomy of discovered works, categorising them according to their intent and contributions. This survey also identifies key technical challenges that GenAI faces in this space, such as domain-specific data scarcity and limited support for integration with existing PCB tools. Finally, future research directions are discussed: our survey shows that there are many opportunities remaining when considering how GenAI may be integrated into various tasks in PCB design and test.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Generative AI
PCB design automation
hardware design
design-for-test
AI integration
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