A Consolidated Approach towards Application of Machine Learning Principles in Additive Manufacturing

Ali Raza, Ali Haider, Waseem Haider

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In recent years, additive manufacturing (AM) has garnered significant attention all over the world due to the exemplary benefits attained during design to achieving superior part quality. Researchers have also started utilizing machine learning (ML) tools to aid the AM process. Emphasis has been laid on the availability of ample datasets and the ease of their acquisition. The need for establishment of feature libraries has been highlighted. Different ML techniques and associated models such as Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Decision Trees (DT), Deep Convolution Network (DNN), and Convolutional Neural Network (CNN) are being used by researchers for optimization of parameters, defect detection, creation of online monitoring systems as well as predicting the powder spreading mechanism for AM. In fact, most ML tools are utilized either for classification or regression purposes. This paper focuses on the availability of the resources required to employ ML in AM, the applications of ML in AM, present limitations, and potential opportunities for extended use in future.

Original languageEnglish
Title of host publication2021 IEEE International Conference on Electro Information Technology, EIT 2021
PublisherIEEE Computer Society
Pages363-368
Number of pages6
ISBN (Electronic)9781665418461
DOIs
StatePublished - May 14 2021
Event2021 IEEE International Conference on Electro Information Technology, EIT 2021 - Mt. Pleasant, United States
Duration: May 14 2021May 15 2021

Publication series

NameIEEE International Conference on Electro Information Technology
Volume2021-May
ISSN (Print)2154-0357
ISSN (Electronic)2154-0373

Conference

Conference2021 IEEE International Conference on Electro Information Technology, EIT 2021
Country/TerritoryUnited States
CityMt. Pleasant
Period05/14/2105/15/21

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