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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Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
2022
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/161922 |
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Institution: | Nanyang Technological University |
Language: | English |