TY  - JOUR
AU  - Alabi, Micheal Omotayo 
AU  - Nixon, Ken 
AU  - Botef, Ionel 
PY  - 2018
TI  - A Survey on Recent Applications of Machine Learning with Big Data in Additive Manufacturing Industry
JF  - American Journal of Engineering and Applied Sciences
VL  - 11
IS  - 3
DO  - 10.3844/ajeassp.2018.1114.1124
UR  - https://thescipub.com/abstract/ajeassp.2018.1114.1124
AB  - 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.