Title | Data-driven generative design for mass customization: A case study |
Author | |
Corresponding Author | Tang, Yunlong; Xiong, Yi |
Publication Years | 2022-10-01
|
DOI | |
Source Title | |
ISSN | 1474-0346
|
EISSN | 1873-5320
|
Volume | 54 |
Abstract | Generative design provides a promising algorithmic solution for mass customization of products, improving both product variety and design efficiency. However, the current designer-driven generative design formulates the automated program in a manual manner and has insufficient ability to satisfy the diverse needs of individuals. In this work, we propose a data-driven generative design framework by integrating multiple types of data to improve the automation level and performance of detail design to boost design efficiency and improve user satisfaction. A computational workflow including automated shape synthesis and structure design methods is established. More specifically, existing designs selected based on user preferences are utilized in the shape synthesis for creating generative models. For structural design, user-product interaction data gathered by sensors are used as inputs for controlling the spatial distributions of heterogeneous lattice structures. Finally, the pro-posed concept and workflow are demonstrated with a bike saddle design with a personalized shape and inner structures to be manufactured with additive manufacturing. |
Keywords | |
URL | [Source Record] |
Indexed By | |
Language | English
|
SUSTech Authorship | First
; Corresponding
|
Funding Project | [52105261]
; [2022A1515010316]
|
WOS Research Area | Computer Science
; Engineering
|
WOS Subject | Computer Science, Artificial Intelligence
; Engineering, Multidisciplinary
|
WOS Accession No | WOS:000886982200001
|
Publisher | |
ESI Research Field | ENGINEERING
|
Data Source | Web of Science
|
Citation statistics |
Cited Times [WOS]:2
|
Document Type | Journal Article |
Identifier | http://kc.sustech.edu.cn/handle/2SGJ60CL/417043 |
Department | School of System Design and Intelligent Manufacturing |
Affiliation | 1.Southern Univ Sci & Technol, Sch Syst Design & Intelligent Mfg, Shenzhen 518055, Peoples R China 2.Guilin Univ Elect Technol, Sch Mech & Elect Engn, Guilin 541004, Peoples R China 3.Guilin Univ Elect Technol, Natl Demonstrat Ctr Expt Elect Circuit Educ, Guilin 541004, Peoples R China 4.Monash Univ, Mech & Aerosp Engn Dept, Melbourne 3168, Australia |
First Author Affilication | School of System Design and Intelligent Manufacturing |
Corresponding Author Affilication | School of System Design and Intelligent Manufacturing |
First Author's First Affilication | School of System Design and Intelligent Manufacturing |
Recommended Citation GB/T 7714 |
Jiang, Zhoumingju,Wen, Hui,Han, Fred,et al. Data-driven generative design for mass customization: A case study[J]. ADVANCED ENGINEERING INFORMATICS,2022,54.
|
APA |
Jiang, Zhoumingju,Wen, Hui,Han, Fred,Tang, Yunlong,&Xiong, Yi.(2022).Data-driven generative design for mass customization: A case study.ADVANCED ENGINEERING INFORMATICS,54.
|
MLA |
Jiang, Zhoumingju,et al."Data-driven generative design for mass customization: A case study".ADVANCED ENGINEERING INFORMATICS 54(2022).
|
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