ハイテクシステム設計のためのAI駆動合成：イノベーションの自動化
AI-Driven Synthesis for High-Tech System Design: Automating Innovation
深層学習と生成AIを用いてシステム設計を自動化するフレームワークを提案し、e-driveシステム設計と空間寸法決定問題の2つのケーススタディで実証した。
著者: Luuk Oerlemans, Steven Westerhof, Theo Hofman
分類: cs.AI, cs.AR, cs.CE, cs.ET, cs.RO
原文アブストラクト
This article addresses the combinatorial complexity inherent in modern high-tech system design by presenting automation-in-design (AiD) as a transformative paradigm. We propose computational design synthesis (CDS), a framework utilising deep learning and generative AI to automate the creation of novel systems. Two case studies (e-drive system design and spatial dimensioning problem) serve as proof-points for this approach. The AI-driven methods used in the case studies represent a fundamental shift in engineering, advancing from simulation-based optimisation towards autonomous design with minimal human supervision.