摘要
结合数控铣床加工质量控制的实际需求,对基于大数据分析的质量预测与自适应调节方法进行研究,阐述通过实时数据采集与分析,优化加工过程中表面粗糙度和尺寸误差的调节机制。经实验验证,该方法能够有效提升加工精度和稳定性,具有较强的自适应能力,能满足不同加工工况的质量控制需求。
Combined with the practical needs of quality control in computer numerical control milling machine machining,the quality prediction and adaptive adjustment methods are studied based on big data analysis,and the adjustment mechanism of optimizing surface roughness and dimensional errors during the machining process is elaborated through real-time data acquisition and analysis.Through experimental verification,this method can effectively improve machining accuracy and stability,and has strong adaptability to meet the quality control requirements of different machining conditions.
作者
杨云辉
YANG Yunhui(Faculty of Mechanical and Electrical Engineering,Yunnan Open University,Kunming 650500)
出处
《现代制造技术与装备》
2025年第12期196-198,共3页
Modern Manufacturing Technology and Equipment
关键词
数控铣床
大数据分析
质量控制
自适应调节
加工精度
computer numerical control milling machine
big data analysis
quality control
adaptive regulation
machining accuracy
