Analysis of CNC machining based on characteristics of thermal errors and optimal design of experimental programs during actual cutting process

详细信息    查看全文

• 作者：En-ming Miao ; Hui Liu ; Kuang-chao Fan…
• 关键词：Thermal error compensation ; Actual cutting ; Taguchi method ; The optimal cutting parameters combination ; CNC
• 刊名：The International Journal of Advanced Manufacturing Technology
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：88
• 期：5-8
• 页码：1363-1371
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Industrial and Production Engineering; Media Management; Mechanical Engineering; Computer-Aided Engineering (CAD, CAE) and Design;
• 出版者：Springer London
• ISSN：1433-3015
• 卷排序：88

文摘

The compensation of thermal errors plays a critical role in developing the machine tools of intelligent computer numerically controlled (CNC). According to the international standards, the testing, modeling, and compensation of thermal error of CNC machine tools are carried out only in a so-called idling state where the spindle is free running without any workload. However, in practical applications, machine tools are often applied in the actual cutting state with more influence factors, such as cutting parameters, cooling liquid, and cutting force. Subsequently, the thermal characteristics at idling state and actual cutting state are compared and analyzed in this paper. It was found that the thermal error compensation model under idling state is not precise enough to be applied in actual cutting state. Also, further research finds that different combinations of cutting parameters, such as spindle speed and feed rate, also have influences on the accuracy of prediction and robustness of thermal error model under actual cutting state. Therefore, the cutting parameters of spindle speed, feed rate, depth of cut, and ambient temperature are studied with the usage of the Taguchi method. Through calculating signal-to-noise ratio (SN) of each combination through residual standard deviation of thermal error model, the combination of optimal cutting parameters can be obtained. The resultant analysis shows that the thermal error model under the combination of optimal cutting parameters demonstrates higher accuracy of prediction and better robustness.