Algorithmic design of a product based on customer data

Detalhes bibliográficos
Autor(a) principal: Francisco, Álvaro Miguel Cruz
Data de Publicação: 2021
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10773/33788
Resumo: There is a growing trend of using computers creatively in order to enrich the design process. There are three Computational Design techniques that stand-out: Parametric Design, Generative Design and Algorithmic Design. This dissertation intends to test the viability of using these techniques in a context of product development. These techniques show tremendous potential for products that can be customizable by consumers, exploring the combination of various manufacturing methods. To achieve these goals a case study with customization potential and the ability to test algorithmic design techniques has been selected. The results originate from 2 approaches: a generative approach and an algorithmic approach, with each having different evaluation methods. The generative approach is able to explore a solution search space and compares the generated curvatures, whilst the algorithmic approach takes advantage of rapid prototyping principles. The performance indicators for the case study’s conception stage using CD techniques are very positive, but the production stage needs more research.
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spelling Algorithmic design of a product based on customer dataParametric designGenerative designAlgorithmic designMass customizationHybrid manufacturingThere is a growing trend of using computers creatively in order to enrich the design process. There are three Computational Design techniques that stand-out: Parametric Design, Generative Design and Algorithmic Design. This dissertation intends to test the viability of using these techniques in a context of product development. These techniques show tremendous potential for products that can be customizable by consumers, exploring the combination of various manufacturing methods. To achieve these goals a case study with customization potential and the ability to test algorithmic design techniques has been selected. The results originate from 2 approaches: a generative approach and an algorithmic approach, with each having different evaluation methods. The generative approach is able to explore a solution search space and compares the generated curvatures, whilst the algorithmic approach takes advantage of rapid prototyping principles. The performance indicators for the case study’s conception stage using CD techniques are very positive, but the production stage needs more research.Cada vez mais os computadores são usados de forma criativa para aprofundar o processo de design. Existem três técnicas de design computacional que merecem destaque: design paramétrico, design generativo e design algorítmico. Este trabalho tem como intuito testar a viabilidade do uso destas técnicas num contexto de desenvolvimento de produto. Estas técnicas demonstram um grande potencial para produtos que possam ser customizáveis, explorando a combinação de diferentes métodos de produção. Para isso foi selecionado um caso de estudo com potencial de customização onde seja possível testar a aplicação das técnicas de design algorítmico. Os resultados provêm de 2 abordagens: uma abordagem generativa e uma abordagem algorítmica, com cada abordagem a ter um método de avaliação de resultados. A abordagem generativa varre um espaço de soluções e compara as curvaturas geradas enquanto a abordagem algorítmica aproveita os princípios de prototipagem rápida. Os indicadores obtidos para a fase de conceção do caso de estudo usando as técnicas de CD foram positivos, no entanto a fase da produção necessita mais investigação.2022-05-03T13:26:46Z2021-11-26T00:00:00Z2021-11-26info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10773/33788engFrancisco, Álvaro Miguel Cruzinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-02-22T12:04:58Zoai:ria.ua.pt:10773/33788Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:05:07.553460Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Algorithmic design of a product based on customer data
title Algorithmic design of a product based on customer data
spellingShingle Algorithmic design of a product based on customer data
Francisco, Álvaro Miguel Cruz
Parametric design
Generative design
Algorithmic design
Mass customization
Hybrid manufacturing
title_short Algorithmic design of a product based on customer data
title_full Algorithmic design of a product based on customer data
title_fullStr Algorithmic design of a product based on customer data
title_full_unstemmed Algorithmic design of a product based on customer data
title_sort Algorithmic design of a product based on customer data
author Francisco, Álvaro Miguel Cruz
author_facet Francisco, Álvaro Miguel Cruz
author_role author
dc.contributor.author.fl_str_mv Francisco, Álvaro Miguel Cruz
dc.subject.por.fl_str_mv Parametric design
Generative design
Algorithmic design
Mass customization
Hybrid manufacturing
topic Parametric design
Generative design
Algorithmic design
Mass customization
Hybrid manufacturing
description There is a growing trend of using computers creatively in order to enrich the design process. There are three Computational Design techniques that stand-out: Parametric Design, Generative Design and Algorithmic Design. This dissertation intends to test the viability of using these techniques in a context of product development. These techniques show tremendous potential for products that can be customizable by consumers, exploring the combination of various manufacturing methods. To achieve these goals a case study with customization potential and the ability to test algorithmic design techniques has been selected. The results originate from 2 approaches: a generative approach and an algorithmic approach, with each having different evaluation methods. The generative approach is able to explore a solution search space and compares the generated curvatures, whilst the algorithmic approach takes advantage of rapid prototyping principles. The performance indicators for the case study’s conception stage using CD techniques are very positive, but the production stage needs more research.
publishDate 2021
dc.date.none.fl_str_mv 2021-11-26T00:00:00Z
2021-11-26
2022-05-03T13:26:46Z
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