AI-Driven Synthesis for High-Tech System Design: Automating Innovation
Luuk Oerlemans, Steven Westerhof, Theo Hofman
cs.AI cs.AR cs.CE cs.ET cs.RO
Abstract
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.
Topics
Classified with taxonomy v2 on Sat, 5 Sept 2026.