Research on Quality Control of Machining Process for High-Precision Automation Components
DOI:
https://doi.org/10.71222/px3p4f48Keywords:
CNC Machining, Quality Control, Surface Integrity, Online Monitoring, Precision EngineeringAbstract
The manufacturing of high-precision automation components, such as precision sensor housings and high-speed interface board structures, demands rigorous quality control to ensure operational reliability in complex industrial environments. This research investigates the intricate relationship between machining process parameters and the resulting quality of the workpiece. By analyzing the fundamental mechanisms through which cutting speed, feed rate, and depth of cut influence dimensional accuracy and surface integrity, including surface roughness and residual stress, this study provides a theoretical foundation for process optimization. A significant portion of the work is dedicated to the development of an advanced online monitoring and deviation compensation model. This model integrates real-time sensor data with sophisticated detection algorithms to achieve micron-level control over dimensional deviations during the machining process. Furthermore, a comprehensive closed-loop process quality control system framework is proposed. This system is designed to mitigate typical machining defects and enhance the fatigue life of components. Experimental results demonstrate that the implementation of this closed-loop framework significantly reduces dimensional errors and improves surface consistency. The findings suggest that the integration of real-time data acquisition with adaptive control algorithms is essential for meeting the stringent requirements of modern automation hardware. Ultimately, this research contributes to the advancement of intelligent manufacturing by providing a robust methodology for maintaining high precision and reliability in the production of critical structural components. By bridging the gap between theoretical parameter analysis and practical real-time application, the study offers a scalable solution for high-end manufacturing sectors.References
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