An analytical model for predicting specific cutting energy in whirling milling process

被引:29
作者
He, Yan [1 ]
Wang, Lexiang [1 ]
Wang, Yulin [2 ]
Li, Yufeng [1 ]
Wang, Shilong [1 ]
Wang, Yan [3 ]
Liu, Chao [1 ]
Hao, Chuanpeng [1 ]
机构
[1] Chongqing Univ, State Key Lab Mech Transmiss, Chongqing 400030, Peoples R China
[2] Nanjing Univ Sci & Technol, Sch Mech Engn, Nanjing 210094, Jiangsu, Peoples R China
[3] Univ Brighton, Dept Comp Math & Engn, Brighton BN2 4GJ, E Sussex, England
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
Whirling milling process; Specific cutting energy; Energy model; Cutting parameters; Material removal rate; MATERIAL REMOVAL; CONSUMPTION; PARAMETERS; OPTIMIZATION; INTEGRITY; POWER;
D O I
10.1016/j.jclepro.2019.118181
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The specific cutting energy (SCE) of machining processes is a significant indicator for machining sustainability. However, the characteristics of SCE in whirling milling as a promising green process are unknown because of the special material removal mechanism of this process. This paper presents an analytical model for predicting SCE based on the material removal mechanism of whirling milling. The cutting parameters affecting the SCE characteristics are identified considering the un-deformed chip formation. An analytical model is developed as functions of the identified cutting parameters by calculating material removal volume and cutting forces. To validate the proposed model, the analytical model was applied in ball screw shaft whirling milling. The results indicate that the analytical model can be effectively used to predict the SCE with over 90% accuracy. In addition, the effects of cutting parameters and material removal rate (MRR) on SCE were investigated and analyzed based on the proposed model, which can provide valuable information and guidance for the optimal selection of cutting parameters to minimize SCE and improve MRR. (C) 2019 Elsevier Ltd. All rights reserved.
引用
收藏
页数:16
相关论文
共 31 条
[1]  
Altintas Y, 2012, MANUFACTURING AUTOMATION: METAL CUTTING MECHANICS, MACHINE TOOL VIBRATIONS, AND CNC DESIGN, 2ND EDITION, P1
[2]   Improving the integrity of specific cutting energy coefficients for energy demand modelling [J].
Balogun, Vincent A. ;
Gu, Heng ;
Mativenga, Paul T. .
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE, 2015, 229 (12) :2109-2117
[3]   Impact of un-deformed chip thickness on specific energy in mechanical machining processes [J].
Balogun, Vincent A. ;
Mativenga, Paul T. .
JOURNAL OF CLEANER PRODUCTION, 2014, 69 :260-268
[4]   ON THE CLOSED-FORM MECHANISTIC MODELING OF MILLING - SPECIFIC CUTTING ENERGY, TORQUE, AND POWER [J].
BAYOUMI, AE ;
YUCESAN, G ;
HUTTON, DV .
JOURNAL OF MATERIALS ENGINEERING AND PERFORMANCE, 1994, 3 (01) :151-158
[5]   Energy benchmarking rules in machining systems [J].
Cai, Wei ;
Liu, Fei ;
Dinolov, Ognyan ;
Xie, Jun ;
Liu, Peiji ;
Tuo, Junbo .
ENERGY, 2018, 142 :258-263
[6]   Optimization of cutting parameters for minimizing energy consumption in turning of AISI 6061 T6 using Taguchi methodology and ANOVA [J].
Camposeco-Negrete, Carmita .
JOURNAL OF CLEANER PRODUCTION, 2013, 53 :195-203
[7]   Identification of the optimum cutting parameters in intermittent hard turning with specific cutting energy, damage equivalent stress, and surface roughness considered [J].
Cui, Xiaobin ;
Guo, Jingxia .
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2018, 96 (9-12) :4281-4293
[8]  
Dahmus J.B., 2004, ASME INT MECH ENG C, DOI [10.1115/IMECE2004-62600, DOI 10.1115/IMECE2004-62600]
[9]  
Fraunhofer, 2012, EC MACH TOOLS TASK 4
[10]   Research on specific cutting energy and parameter optimization in micro-milling of heat-resistant stainless steel [J].
Gao, Shoufeng ;
Pang, Siqin ;
Jiao, Li ;
Yan, Pei ;
Luo, Zhiwen ;
Yi, Jie ;
Wang, Xibin .
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2017, 89 (1-4) :191-205