Investigation of the tool flank wear influence on cutter-workpiece engagement and cutting force in micro milling processes

被引:14
作者
Gao, Shuaishuai [1 ,2 ]
Duan, Xianyin [1 ]
Zhu, Kunpeng [1 ,2 ]
Zhang, Yu [1 ]
机构
[1] Wuhan Univ Sci & Technol, Sch Machinery & Automat, Wuhan 430081, Peoples R China
[2] Chinese Acad Sci, Hefei Inst Phys Sci, Inst Intelligent Machines, Changzhou 213164, Peoples R China
基金
中国国家自然科学基金;
关键词
Micro-milling; Cutting force modeling; Cutter-workpiece engagement; Tool wear; Tool cutting edge radius; Micro-cutting; PART II; MODEL; PREDICTION; OPERATIONS; DEFLECTION;
D O I
10.1016/j.ymssp.2024.111104
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Cutting force modeling is essential for comprehending the dynamic mechanics of the micromilling process. Accurate calculation of the cutter-workpiece engagement is crucial for predicting cutting force accurately. This study proposes an accurate analytical model of cutter-workpiece engagement that comprehensively incorporates tool flank wear, tool edge radius, and tool runout for predicting cutting forces in the micro-milling process. Based on the actual tool radius model, which takes into account tool flank wear and tool edge radius, a fast real-time online method for accurately calculating the entry and exit angles is presented. This method involves the trochoidal trajectories of the current cutting edge and all passing cutting edges from the previous cycle under the influence of tool runout. Then the cutter-workpiece engagement is determined. Based on this, the cutting force is predicted combined with instantaneous uncut chip thickness and cutting force coefficients considering tool flank wear and tool runout. Through micro-end milling experiments, the validity of the cutting force model is confirmed. The statistical analysis of the predicted cutting forces further demonstrates the effectiveness of accounting for the impact of tool flank wear on the cutting forces throughout the entire micro-milling process. Through case analysis, it is concluded that tool flank wear leads to increased cutter-workpiece engagement and significantly affects the cutting forces in three directions. This work could offer a theoretical foundation and practical guidance for predicting tool life and controlling surface quality during the machining process.
引用
收藏
页数:17
相关论文
共 46 条
[1]   Protocol for tool wear measurement in micro-milling [J].
Alhadeff, L. L. ;
Marshall, M. B. ;
Curtis, D. T. ;
Slatter, T. .
WEAR, 2019, 420 :54-67
[2]  
Altintas Y, 2012, MANUFACTURING AUTOMATION: METAL CUTTING MECHANICS, MACHINE TOOL VIBRATIONS, AND CNC DESIGN, 2ND EDITION, P1
[3]   A review on micro-milling: recent advances and future trends [J].
Balazs, Barnabas Zoltan ;
Geier, Norbert ;
Takacs, Marton ;
Davim, J. Paulo .
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2021, 112 (3-4) :655-684
[4]   Modeling micro-end-milling operations. Part II: tool run-out [J].
Bao, WY ;
Tansel, IN .
INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE, 2000, 40 (15) :2175-2192
[5]   Modeling micro-end-milling operations. Part III: influence of tool wear [J].
Bao, WY ;
Tansel, IN .
INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE, 2000, 40 (15) :2193-2211
[6]   Advances in micro milling: From tool fabrication to process outcomes [J].
Chen, Ni ;
Li, Hao Nan ;
Wu, Jinming ;
Li, Zhenjun ;
Li, Liang ;
Liu, Gongyu ;
He, Ning .
INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE, 2021, 160
[7]  
Davim J.P., 2014, MODERN MECH ENG RES
[8]   Real-time reliability analysis of micro-milling processes considering the effects of tool wear [J].
Ding, Pengfei ;
Huang, Xianzhen ;
Li, Shangjie ;
Zhao, Chengying ;
Zhang, Xuewei .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2023, 200
[9]   Online monitoring model of micro-milling force incorporating tool wear prediction process [J].
Ding, Pengfei ;
Huang, Xianzhen ;
Zhao, Chengying ;
Liu, Huizhen ;
Zhang, Xuewei .
EXPERT SYSTEMS WITH APPLICATIONS, 2023, 223
[10]   Unsupervised online prediction of tool wear values using force model coefficients in milling [J].
Dou, Jianming ;
Jiao, Shengjie ;
Xu, Chuangwen ;
Luo, Foshu ;
Tang, Linhu ;
Xu, Xinxin .
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2020, 109 (3-4) :1153-1166