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

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.