Data-Driven Performance-Based Generative Design and Digital Fabrication for Industry 4.0: Precedent Work, Current Progress, and Future Prospects

Ding Wen Bao, Xiao Yan

Lecture notes in mechanical engineering(2023)

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摘要
With the development of computing technology, architectural design has been impacted and changed significantly over the past decade. It led us to rethink the new design methodology and application, such as the data-driven performance-based design method and its relevant digital fabrication for Industry 4.0. The paper explores the theories and practices of “Overall Structure Performance Data-Driven Design” and “Swarm Intelligence-Based Architectural Design” by collecting, reviewing, and analyzing cutting-edge design methodologies and proposes a new algorithm framework that combines performance data with agent-based modelling for design. The paper demonstrates the original process and iterative argument affiliated with the “Multi-Agent-Based Topology Optimization” (MATO) method, as proposed by Bao and Yan in 2021, which has the potential to provide a new path for the future computational design of buildings. Finally, the paper concludes with an analytical study and future expectations for complex bionic morphology digital fabrication generated by the related methodology above.
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关键词
digital fabrication,generative design,data-driven,performance-based
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