An Explorative Study of AI Applications in Composite Material Extrusion Additive Manufacturing

被引:0
作者
Harper, Austin [1 ]
Wuest, Thorsten [1 ,2 ]
机构
[1] West Virginia Univ, IMSE Dept, Morgantown, WV 26506 USA
[2] Univ South Carolina, Dept Mech Engn, Columbia, SC 29208 USA
来源
ADVANCES IN PRODUCTION MANAGEMENT SYSTEMS-PRODUCTION MANAGEMENT SYSTEMS FOR VOLATILE, UNCERTAIN, COMPLEX, AND AMBIGUOUS ENVIRONMENTS, APMS 2024, PT IV | 2024年 / 731卷
关键词
Material Extrusion; Additive Manufacturing; Machine Learning; Artificial Intelligence; Carbon-Fiber Reinforced Polymers;
D O I
10.1007/978-3-031-71633-1_17
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Additive Manufacturing (AM) is on the forefront of innovative advance manufacturing techniques leveraging Artificial Intelligence (AI) and Machine Learning (ML) to improve processing capabilities. We conducted a literature review to survey the current state of the art for AI/ML applications within Material Extrusion AM (MEX-AM). Furthermore, this study explored the intersection of AI applications and use of Carbon Fiber-Reinforced Polymers (CFRP) as a MEX-AM material. We found that while discontinuous CFRPs are covered in several experimental studies, there was a noticeable lack of research on continuous CFRPs among the collected papers. We found that the most common ML Solution for quality issues in MEX-AM was the artificial neural network feed forward supervised learning back propagation (ANN-FFNN-SL-BPN) Solution.
引用
收藏
页码:233 / 247
页数:15
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