A comprehensive review of machine learning techniques in computer numerical controlled machines

Pagadipala srikanth, Pulimamidi sai teja, Borigam Lakshmi prasad and Veduruvada pavan kalyan *

Department Of Mechanical Engineering, Vignan institute of technology and science, Deshmuki (V), Pochampally (M), Yadadri Bhuvanagiri Dist, Telangana-508204, India.
 
Review
International Journal of Science and Research Archive, 2023, 09(01), 627–637.
Article DOI: 10.30574/ijsra.2023.9.1.0491
Publication history: 
Received on 13 May 2023; revised on 22 June 2023; accepted on 25 June 2023
 
Abstract: 
Machine learning (ML) is significant advancements in computer science and data processing systems that may be utilized to improve almost all technology-enabled services, goods, and industrial applications. Machine learning is a branch of computer science and artificial intelligence. It emphasizes the use of data and algorithms to mimic the learning process of machines and improve system accuracy. To extend the life of the cutting tools used in machining processes, machine learning algorithms may be used to forecast cutting forces and cutting tool wear. In order to improve productivity during the component production processes, optimized machining parameters for CNC machining operations may be obtained by applying cutting-edge machine learning algorithms. Furthermore, the appearance of Advanced machine learning algorithms can forecast and enhance machinable components to raise the caliber of machinable parts. Machine learning is applied to prediction approaches of energy consumption of CNC machine tools in order to analyses and minimize power usage during CNC machining processes. The use of machine learning and artificial intelligence systems in CNC machine tools is examined in this paper, and future research projects are also suggested in order to offer an overview of the most recent studies on these topics. As a result, the research filed can be moved forward by reviewing and analyzing recent achievements in published papers to offer innovative concepts and approaches in applications of machine learning in CNC machine tools.
 
Keywords: 
Machine learning; CNC; Neural Network Tool; Optimization; Surface Roughness; Cutting force
 
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