Multidisciplinary design optimization in design for additive manufacturing

Liu, Guang1; Xiong, Yi1,2; Rosen, David W.2,3

2022-02-01

10.1093/jcde/qwab073

JOURNAL OF COMPUTATIONAL DESIGN AND ENGINEERING   影响因子和分区

2288-5048

Design for additive manufacturing (AM) involves decision making in various design domains, including product design, material selection, and process planning. In practice, engineers typically adopt a sequential design process to optimize these design domains in consecutive order. However, coupling factors, e.g. shared variables, related constraints, and conflicting objectives, are not sufficiently considered within the sequential design process, resulting in an inefficient workflow and suboptimal design solutions. To address the above issues, this paper proposes a multidisciplinary design optimization framework to simultaneously optimize different domains, which enables rapid exploration and complete exploitation of the AM design space under complex constraints. More specifically, the proposed framework is based on the concurrent optimization method, which coordinates the optimization of different design domains by allowing an automated exchange of design information. Also, the framework utilizes the surrogate modeling approach to approximate high-fidelity simulations for facilitating the iterative process. The effectiveness of the proposed framework is validated with two examples, a plate with a hole design and a hook design, which involve multiple design objectives from both process and structure domains, i.e. the print time, print area, strain energy, and maximum von Mises stress.

design for additive manufacturing multidisciplinary design optimization concurrent engineering design theory and methodology

SCI ; EI

英语

第一 ; 通讯

National Key R&D Program of China[2021YFB1715400] ; National Natural Science Foundation of China[52105261] ; Shenzhen Science and Technology Innovation Committee[JCYJ20210324104610028]

Computer Science ; Engineering

Computer Science, Interdisciplinary Applications ; Engineering, Multidisciplinary

WOS:000742024000008

OXFORD UNIV PRESS

20220811700709

3D printers ; Additives ; Decision making ; Design aids ; Design for manufacturability ; Iterative methods ; Product design ; Strain energy

Computer Applications:723.5 ; Printing Equipment:745.1.1 ; Chemical Agents and Basic Industrial Chemicals:803 ; Engineering Graphics:902.1 ; Management:912.2 ; Production Engineering:913.1 ; Manufacturing:913.4 ; Product Development; Concurrent Engineering:913.6 ; Numerical Methods:921.6 ; Mechanics:931.1

Web of Science

1.Southern Univ Sci & Technol, Sch Syst Design & Intelligent Mfg, Shenzhen 518055, Peoples R China
2.Singapore Univ Technol & Design, Digital Mfg & Design DManD Ctr, Singapore 487372, Singapore
3.Georgia Inst Technol, GW Woodruff Sch Mech Engn, Atlanta, GA 30332 USA

Liu, Guang,Xiong, Yi,Rosen, David W.. Multidisciplinary design optimization in design for additive manufacturing[J]. JOURNAL OF COMPUTATIONAL DESIGN AND ENGINEERING,2022,9(1):128-143.

Liu, Guang,Xiong, Yi,&Rosen, David W..(2022).Multidisciplinary design optimization in design for additive manufacturing.JOURNAL OF COMPUTATIONAL DESIGN AND ENGINEERING,9(1),128-143.

Liu, Guang,et al."Multidisciplinary design optimization in design for additive manufacturing".JOURNAL OF COMPUTATIONAL DESIGN AND ENGINEERING 9.1(2022):128-143.