Details
| Originalsprache | Englisch |
|---|---|
| Aufsatznummer | 012035 |
| Fachzeitschrift | IOP Conference Series: Materials Science and Engineering |
| Jahrgang | 408 |
| Publikationsstatus | Elektronisch veröffentlicht (E-Pub) - 1 Okt. 2018 |
| Veranstaltung | 2018 2nd International Conference on Advanced Technologies in Design, Mechanical and Aeronautical Engineering, ATDMAE 2018 - Dalian, China Dauer: 1 Juli 2018 → 3 Juli 2018 |
Abstract
Design problems with variable requirements force designers to explore multiple alternatives between problem space and solution space of a design task. Despite several methods have been already proposed, CAD models hardly meet these variable requirements. To close this research gap, this study develops a generative design approach, addressing the automation of designing alternatives by capturing design knowledge into a set of design elements. These elements use essentially knowledge-based parametrics in terms of design requirements. Such design elements are used to assist designers in the creation of required design variants. Thus, the exploration of design alternatives is transformed into configuration of desired design elements. As a result, the invested time in routine work is reduced and designers are able to concentrate on the exploration of required design alternatives. Moreover, the output configuration also offers potentials in computer-aided optimization, since the design elements not only capture the design knowledge, but also incorporate manufacturing restrictions. At last, this approach is illustrated by taking a bicycle peddle crank as an example.
ASJC Scopus Sachgebiete
- Werkstoffwissenschaften (insg.)
- Allgemeine Materialwissenschaften
- Ingenieurwesen (insg.)
- Allgemeiner Maschinenbau
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in: IOP Conference Series: Materials Science and Engineering, Jahrgang 408, 012035, 01.10.2018.
Publikation: Beitrag in Fachzeitschrift › Konferenzaufsatz in Fachzeitschrift › Forschung › Peer-Review
}
TY - JOUR
T1 - Generative Design Approach for Modeling Creative Designs
AU - Li, Haibing
AU - Lachmayer, Roland
PY - 2018/10/1
Y1 - 2018/10/1
N2 - Design problems with variable requirements force designers to explore multiple alternatives between problem space and solution space of a design task. Despite several methods have been already proposed, CAD models hardly meet these variable requirements. To close this research gap, this study develops a generative design approach, addressing the automation of designing alternatives by capturing design knowledge into a set of design elements. These elements use essentially knowledge-based parametrics in terms of design requirements. Such design elements are used to assist designers in the creation of required design variants. Thus, the exploration of design alternatives is transformed into configuration of desired design elements. As a result, the invested time in routine work is reduced and designers are able to concentrate on the exploration of required design alternatives. Moreover, the output configuration also offers potentials in computer-aided optimization, since the design elements not only capture the design knowledge, but also incorporate manufacturing restrictions. At last, this approach is illustrated by taking a bicycle peddle crank as an example.
AB - Design problems with variable requirements force designers to explore multiple alternatives between problem space and solution space of a design task. Despite several methods have been already proposed, CAD models hardly meet these variable requirements. To close this research gap, this study develops a generative design approach, addressing the automation of designing alternatives by capturing design knowledge into a set of design elements. These elements use essentially knowledge-based parametrics in terms of design requirements. Such design elements are used to assist designers in the creation of required design variants. Thus, the exploration of design alternatives is transformed into configuration of desired design elements. As a result, the invested time in routine work is reduced and designers are able to concentrate on the exploration of required design alternatives. Moreover, the output configuration also offers potentials in computer-aided optimization, since the design elements not only capture the design knowledge, but also incorporate manufacturing restrictions. At last, this approach is illustrated by taking a bicycle peddle crank as an example.
UR - http://www.scopus.com/inward/record.url?scp=85055281304&partnerID=8YFLogxK
U2 - 10.1088/1757-899X/408/1/012035
DO - 10.1088/1757-899X/408/1/012035
M3 - Conference article
AN - SCOPUS:85055281304
VL - 408
JO - IOP Conference Series: Materials Science and Engineering
JF - IOP Conference Series: Materials Science and Engineering
SN - 1757-8981
M1 - 012035
T2 - 2018 2nd International Conference on Advanced Technologies in Design, Mechanical and Aeronautical Engineering, ATDMAE 2018
Y2 - 1 July 2018 through 3 July 2018
ER -