A data-driven framework to predict fused filament fabrication part properties using surrogate models and multi-objective optimisation

In additive manufacturing (AM), due to large number of process parameters and multiple responses of interest, it is hard for AM designers to attain optimal part performance without a systematic approach. In this research, a data-driven framework is proposed to achieve the desired AM part performance...

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Bibliographic Details
Main Authors: Zhang, Yongjie, Choi, Joon Phil, Moon, Seung Ki
Other Authors: School of Mechanical and Aerospace Engineering
Format: Article
Language:English
Published: 2022
Subjects:
Online Access:https://hdl.handle.net/10356/161922
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Institution: Nanyang Technological University
Language: English