Exploiting the generative design potential to select the best conceptual design of an aerospace component to be produced by additive manufacturing

被引:10
作者
Pilagatti, Adriano Nicola [1 ]
Atzeni, Eleonora [1 ]
Salmi, Alessandro [1 ]
机构
[1] Politecn Torino, Dept Management & Prod Engn DIGEP, Corso Duca Abruzzi 24, I-10129 Turin, Italy
关键词
Additive manufacturing; Generative design; Design methodology; Laser-powder bed fusion; MECHANICAL-PROPERTIES; LASER; OPTIMIZATION;
D O I
10.1007/s00170-023-11259-7
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Since the advent of Industry 4.0, the manufacturing sector has had to face new challenges, which require the development of new skills and innovative tools. This scenario includes innovative production processes such as additive manufacturing (AM), a technology capable of producing a component layer-by-layer directly from the 3D model without needing specific tools during the building phase. Generative design (GD) may represent an opportunity to maximise the potential of AM techniques. GD is based on parametric computer-aided design (CAD) tools capable of generating multiple optimised outputs, among which the designer could select the most promising solution. This paper presents a general methodology for evaluating the GD outputs in the conceptual phase of design to select the best possible solution through a series of criteria at several levels. The evaluation method is deployed in an aerospace field case study. The procedure demonstrates the benefits of synergising GD with AM in the early stages of product development. This indicates that the developed methodology could reduce the number of iterations during the design process, and the result is a decrease in the overall time spent on the project, avoiding problems during the final stages of the design.
引用
收藏
页码:5597 / 5612
页数:16
相关论文
共 79 条
[1]  
AIA-Aerospace Industries Association, 2020, REC GUID CERT AM COM
[2]  
All3DP, 2022, BEST GEN DES SOFTW 2
[3]  
Altair Engineering Inc, 2017, OPTISTRUCT VER PROBL
[4]   Economics of additive manufacturing for end-usable metal parts [J].
Atzeni, Eleonora ;
Salmi, Alessandro .
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2012, 62 (9-12) :1147-1155
[5]  
Autodesk Inc, 2022, PROD DOC
[6]  
Autodesk Inc, 2021, AUT NETF
[7]  
Autodesk Inc, 2022, MESH
[8]  
Bacus J, 2020, DIGITAL SKETCHING CO
[9]  
Bagassi S., 2016, 30 C INT COUNCIL AER
[10]  
Barnes J., 2016, POWDERMET 2016 INT C