American Journal of Engineering and Applied Sciences

A Survey on Recent Applications of Machine Learning with Big Data in Additive Manufacturing Industry

Micheal Omotayo Alabi, Ken Nixon and Ionel Botef

DOI : 10.3844/ajeassp.2018.1114.1124

American Journal of Engineering and Applied Sciences

Volume 11, Issue 3

Pages 1114-1124

Abstract

Additive Manufacturing (AM) which is also known as 3D printing technology; is recognized as a new paradigm for manufacturing industry. Additive manufacturing is rapidly expanding across different sectors such as healthcare, electronics, automotive, science and engineering, education, dental, etc. Machine Learning and Big Data are both emerging technologies which are becoming popular and gaining more attention from the industries and academic. Machine Learning is a growing field of Artificial Intelligence (AI) that allows systems to learn from data, identify patterns and make decisions with very little human involvement. On the other hand, Big Data is referred to as datasets whose size is more than the capacity of what a conventional database software tools can capture, store, manage and analyze. Lately, Machine Learning techniques and Big Data Analytics are being applied to various applications of additive manufacturing to monitor building process and enhance decisions making using data generated through different sensors or cameras. This paper explores recent applications of Machine Learning with Big Data in the field of additive manufacturing, for instance, application of machine learning in detecting defect or anomaly during build process in additive manufacturing/3D printing machine.

Copyright

© 2018 Micheal Omotayo Alabi, Ken Nixon and Ionel Botef. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.