Artificial Intelligence and Machine Learning Applied to CNC Machining: Perspectives for Industry 4.0

Abstract

Computer Numerical Control (CNC) machining is one of the foundations of modern manufacturing, and its efficiency has been enhanced through the use of Artificial Intelligence and Machine Learning. This paper presents a literature review on the main applications and challenges related to the use of Artificial Intelligence in CNC machining processes. The goal is to consolidate current knowledge on how algorithms focused on toolpath optimization, predictive maintenance, and process planning are being applied. The methodology involved analyzing scientific articles that explore the use of neural networks to improve efficiency, quality, and cost reduction in machining operations. The studies show that Artificial Intelligence helps extend tool life, reduce production time, improve surface finish, and prevent machine downtime. However, despite these advances, there are significant challenges to Artificial Intelligence adoption, such as high implementation costs, the need for reliable data, model complexity, lack of standardization, and organizational resistance to change. It is concluded that, despite these barriers, the use of Artificial Intelligence represents an inevitable and promising path for smart manufacturing, requiring investments both in technology and in workforce training.