Machine learning approach for biological pattern based shell structures

E. Giannopoulou, P. Baquero, A. Warang, A. T. Estévez

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

1 Citation (Scopus)

Abstract

Following previous research towards the subject of digital fabrication of thin shell structures, architectural generative design processes sharing similar physical and geometrical characteristics with biological processes were translated to fabrication processes, blurring the lines between physical, digital and biological, and allowed to examine the structural efficiency of segmented stripes arrangements of complex surfaces with less material usage. The goal of this paper is to examine the efficiency of implementing a machine learning approach into an already established design workflow and to develop a creative methodology for decision making. In order to specify the appropriate features, we look at related work that integrates machine learning inside the design and fabrication process.

Original languageEnglish
Title of host publicationIndustry 4.0 - Shaping The Future of The Digital World - Proceedings of the 2nd International Conference on Sustainable Smart Manufacturing, S2M 2019
EditorsPaulo Jorge da Silva Bartolo, Fernando Moreira da Silva, Shaden Jaradat, Helena Bartolo
PublisherCRC Press/Balkema
Pages79-83
Number of pages5
ISBN (Electronic)9780367422721
Publication statusPublished - 2019
Externally publishedYes
Event2nd International Conference on Sustainable Smart Manufacturing, S2M 2019 - Manchester, United Kingdom
Duration: 9 Apr 201911 Apr 2019

Publication series

NameIndustry 4.0 - Shaping The Future of The Digital World - Proceedings of the 2nd International Conference on Sustainable Smart Manufacturing, S2M 2019

Conference

Conference2nd International Conference on Sustainable Smart Manufacturing, S2M 2019
Country/TerritoryUnited Kingdom
CityManchester
Period9/04/1911/04/19

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