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Open Access
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Ashwini Kumar Baluguri, Srinivasa Rao Seeram
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- Research Scholar, Professor, Department of Mechanical Engineering, KLEF University, Department of Mechanical Engineering, KLEF University, Andhra Pradesh, Andhra Pradesh, India, India
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Abstract
nIn the realm of tabletop multipurpose CNC machines, the integration of machine learning represents a groundbreaking advancement potentially revolutionary in the field of desktop manufacturing. This research explores the seamless incorporation of machine learning algorithms into tabletop CNC machines to enhance their capabilities, performance, and user experience. Through case studies and examples, we demonstrate the profound impact of machine learning integration in key areas of CNC machining, such as accurate tool wear prediction, real-time error detection and compensation, and precise quality control and inspection. The findings highlight the transformative power of machine learning in expanding the horizons of tabletop CNC machines, empowering users with unprecedented precision, efficiency, and versatility. By unraveling the challenges and opportunities associated with machine learning integration, this research paves the way for future developments that will propel tabletop multipurpose CNC machines into an era of intelligent, autonomous, and user-centric manufacturing systems. In addition, real-time feedback and monitoring during the machining process are made possible by the machine learning integration. The system can detect anomalies, such as tool deflection or material inconsistencies, and autonomously make corrective adjustments, ensuring a higher quality output. Additionally, the model continually learns from each machining operation, contributing to an evolving database of best practices for different materials and machining scenarios.
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Keywords: Machine learning, user-centric manufacturing, CNC machining, tabletop, algorithms, error detection.
n[if 424 equals=”Regular Issue”][This article belongs to Journal of Polymer and Composites(jopc)]
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References
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397–410. - Anuar, S. N., Ibrahim, M. H. I., Bahari, A. R., & Rasid, M. F. A. (2020). Integration of machine learning techniques into CNC machining for surface roughness prediction: A review. International Journal of Advanced Manufacturing Technology, 104(1-4), 133–149.
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| Volume | 11 |
| [if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”]Special Issue[/if 424] | 08 |
| Received | November 27, 2023 |
| Accepted | January 5, 2024 |
| Published | March 15, 2024 |
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