Smart Manufacturing through Machine Learning: A Review, Perspective, and Future Directions to the Machining Industry

被引:13
作者
Rajesh, A. S. [1 ]
Prabhuswamy, M. S. [2 ]
Krishnasamy, Srinivasan [1 ]
机构
[1] JSS Sci & Technol Univ, Dept Mech Engn, Mysuru 570006, Karnataka, India
[2] Arba Minch Univ, Arba Minch, Ethiopia
来源
JOURNAL OF ENGINEERING | 2022年 / 2022卷
关键词
PREDICTION;
D O I
10.1155/2022/9735862
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Nowadays, to reach progressive growth although being competitive in the market, the manufacturing industries are using advanced technologies such as cloud computing, the Internet of things (IoT), artificial intelligence, 3D printer, nanotechnology, cryogenics, robotics, and automation in smart manufacturing sectors. One such subclass of artificial intelligence is machine learning, which uses a computer system for making predictions and performing definite tasks without any use of specific instructions to enhance the quality of the product, and rate of production, and to optimize the processes and parameters in machining operations. A broad category of manufacturing that is technology-driven utilizes internet-connected machines to monitor the performances of manufacturing processes referring as smart manufacturing. The current paper presents a comprehensive survey and summary of different machine learning algorithms which are being employed in various traditional and nontraditional machining processes, and also, an outlook of the manufacturing paradigm is presented. Subsequently, future directions in the machining industry were proposed based on trends and challenges that are accompanying machine learning.
引用
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页数:6
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