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Bendilicious

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Maria Smigielska
added 2 research items
This paper presents the results of independent research that aims to investigate the potential and methodology of using Machine Learning (ML) algorithms for precision control of material deformation and increased geometrical and structural performances in robotic rod bending technology (RBT). Another focus lies in integrative methods where design, material properties analysis, structural analysis, optimization and fabrication of robotically rod bended space-frames are merged into one coherent data model and allows for bi-directional information flows, shifting from absolute dimensional architectural descriptions towards the definition of relational systems. The working methodology thus combines robotic RBT and ML with integrated fabrication methods as an alternative to over-specialized and enclosed industrial processes. A design project for the front desk of a gallery in Paris serves as a proof of concept of this research and becomes the starting point for future developments of this methodology.
The Means is an abstract representation of a column as an architectural artefact, as well as a demonstrator of novel computational design methods and alternative post-industrial production process by employing generative design and machine learning for material control. It is the aggregate of generic element as manufactured steel rod, which is a subject of differentiation through the process of robotic rod bending, as a part of a research led by the author (bendilicious.com). As an architectural entity, it stands in opposition to historical orders that has been ruling the column's composition and proportion and as such it is placed in contemporary, purely representational setup of outer delineation with no structural or style capacities. The project addresses the idea of a synthethic role of an architect being a designer, curator and a builder.