arXiv:2606.17074cs.ARcs.AI2026-06

综述生成式AI在印制电路板全流程中的应用与挑战

Surveying GenAI-based Automation in Printed Circuit Board Design and Test

论文配图:Surveying GenAI-based Automation in Printed Circuit Board Design and Test
图 1 · 摘自论文原文
  • 系统梳理GenAI在PCB设计全周期的应用
  • 发现领域数据稀缺和工具集成难是主要瓶颈
  • 适合关注硬件自动化与AI融合的研究者

生成式人工智能(GenAI)在软硬件开发中日益普及,有望减少复杂系统发布前的手动工作量。尽管现有研究多聚焦于集成电路设计自动化,特别是硬件描述语言领域,但其他硬件类型同样重要。本文聚焦生成式AI在印制电路板(PCB)设计生命周期中的应用,涵盖供应链、系统规格、电路设计、布局优化、验证测试、装配与分发等环节。通过分析现有文献,构建了基于意图与贡献的分类体系,并识别出关键挑战:领域特定数据稀缺、对现有PCB工具支持不足。最后讨论未来研究方向,指出在将GenAI融入PCB设计与测试各环节仍有大量机遇待挖掘。

原文摘要 · Abstract (English)

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.

生成式AIPCB设计自动化硬件智能化

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