Optimization of cutting depth parameters to achieve stability in the machining process

The study investigates the effects of cutting depth on machining outcomes through experimental analysis, numerical simulations, and advanced monitoring techniques. Key findings highlight the role of cutting depth in governing cutting forces, heat generation, and vibration behavior, with implications for tool wear and machining precision. The integration of digital twin technology, stability prediction tools, and real-time monitoring systems, such as piezoresistive sensors and vibration analysis, enables optimization of machining conditions for improved productivity and reliability. Results demonstrate that achieving an optimal balance between material removal rates and process stability is crucial for sustainable and efficient machining. Furthermore, this research underscores the importance of considering material properties, tool geometry, and machine rigidity in parameter optimization. The proposed strategies and insights contribute to advancing precision machining practices and enhancing industrial applications.

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Publication Details

Journal
E3S Web of Conferences
Published
2025-01-01
DOI
https://doi.org/10.1051/e3sconf/202562704009
Primary Topic
Advanced machining processes and optimization
Type
article
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article

Optimization of cutting depth parameters to achieve stability in the machining process

Nasillo Urinov, Oybek Tuyboyov, Mehriban Aliyeva, Zayniddin Muxiddinov et al.
E3S Web of Conferences
Advanced machining processes and optimization
article

Optimization of cutting depth parameters to achieve stability in the machining process

Nasillo Urinov, Oybek Tuyboyov, Mehriban Aliyeva, Zayniddin Muxiddinov, Shamiliddin Sirojidinov
article en

Abstract

The study investigates the effects of cutting depth on machining outcomes through experimental analysis, numerical simulations, and advanced monitoring techniques. Key findings highlight the role of cutting depth in governing cutting forces, heat generation, and vibration behavior, with implications for tool wear and machining precision. The integration of digital twin technology, stability prediction tools, and real-time monitoring systems, such as piezoresistive sensors and vibration analysis, enables optimization of machining conditions for improved productivity and reliability. Results demonstrate that achieving an optimal balance between material removal rates and process stability is crucial for sustainable and efficient machining. Furthermore, this research underscores the importance of considering material properties, tool geometry, and machine rigidity in parameter optimization. The proposed strategies and insights contribute to advancing precision machining practices and enhancing industrial applications.

E3S Web of ConferencesVol. 627
Tashkent State Technical University named after Islam Karimov (UZ), Bukhara State University (UZ)
Openalex Percentile: Top 90%
Advanced machining processes and optimization
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