Author: Dr. Vikram Singh, Ms. Anjali Verma,
ABSTRACT: The integration of Artificial Intelligence (AI) with Computer Numerical Control (CNC) programming has introduced novel advancements in tool path optimization, leading to enhanced machining efficiency and precision. This paper investigates AI-assisted algorithms for optimizing CNC tool paths to minimize machining time, reduce tool wear, and improve surface quality. Various AI techniques, including genetic algorithms, neural networks, and reinforcement learning, are reviewed for their applicability in CNC programming. A comparative analysis based on simulation results is presented, highlighting the benefits and challenges of AI-driven tool path strategies. The study concludes with future perspectives on the role of AI in revolutionizing CNC machining processes.
KEYWORDS: AI-Assisted CNC, Tool Path Optimization, Genetic Algorithms, Neural Networks, Reinforcement Learning, Machining Efficiency
Full Issue
| View or download the full issue | PDF 31-35 |