GENDE (http://www.gende.it) is a tool to allow designers, but also com- mon people, to automatically design new products that evolve according to the prin- ciples of Genetic Algorithms (GAs). The selection of the products that will actually take part to the evolutionary process, relies on crowdsourcing mechanisms: only the most appreciated products survive. In the era of 3D-printing, GENDE can pave the way to a completely new class of mass products in which personalization become intrinsic to the design process and is driven by common users rather than being con- fined in the later stages of production and in the hands of professional designers. While GENDE has been originally thought as an automatic design tool, its unique process that involves users from the beginning of the design, can also be used as a powerful marketing tool.

GENDE: GENetic DEsign: Best products evolve according to users feedback / Vitaletti, Andrea. - 413(2017), pp. 101-110. - LECTURE NOTES IN ELECTRICAL ENGINEERING. [10.1007/978-3-319-48511-9_9].

GENDE: GENetic DEsign: Best products evolve according to users feedback

VITALETTI, Andrea
2017

Abstract

GENDE (http://www.gende.it) is a tool to allow designers, but also com- mon people, to automatically design new products that evolve according to the prin- ciples of Genetic Algorithms (GAs). The selection of the products that will actually take part to the evolutionary process, relies on crowdsourcing mechanisms: only the most appreciated products survive. In the era of 3D-printing, GENDE can pave the way to a completely new class of mass products in which personalization become intrinsic to the design process and is driven by common users rather than being con- fined in the later stages of production and in the hands of professional designers. While GENDE has been originally thought as an automatic design tool, its unique process that involves users from the beginning of the design, can also be used as a powerful marketing tool.
2017
Business Models and ICT Technologies for the Fashion Supply Chain. Proceedings of IT4Fashion 2016
978-3-319-48510-2
978-3-319-48511-9
Crowd sourcing; Genetic algorithms; Interactive design; Participatory design; Industrial and Manufacturing Engineering
02 Pubblicazione su volume::02a Capitolo o Articolo
GENDE: GENetic DEsign: Best products evolve according to users feedback / Vitaletti, Andrea. - 413(2017), pp. 101-110. - LECTURE NOTES IN ELECTRICAL ENGINEERING. [10.1007/978-3-319-48511-9_9].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/974709
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