Simulation and Experimental Analysis of Tool Wear and Surface Roughness in Laser Assisted Machining of Titanium Alloy

被引:5
|
作者
Kong, Xianjun [1 ]
Dang, Zhanpeng [1 ]
Liu, Xiaole [1 ]
Wang, Minghai [1 ]
Hou, Ning [1 ]
机构
[1] Shenyang Aerosp Univ, Sch Mechatron Engn, Shenyang 110136, Peoples R China
关键词
DEFORM-3D; LAM; TC6 titanium alloy; tool wear; surface roughness;
D O I
10.3390/cryst13010040
中图分类号
O7 [晶体学];
学科分类号
0702 ; 070205 ; 0703 ; 080501 ;
摘要
A three-dimensional cutting simulation prediction model based on DEFORM-3D finite element software was developed and experimentally validated, with a maximum error of 21.1% between the experimental and simulation results. The effects of the difference in cutting mechanism between conventional machining (CM) and laser-assisted machining (LAM) of TC6 titanium alloy on the tool wear and the surface roughness were investigated in terms of the cutting force and the cutting temperature. The depth of the laser-heated layer was mainly responsible for the difference in the cutting mechanism between the two methods. When the depth of the heating layer was smaller than the cutting depth, the tool wear of the LAM was larger than that of the CM. When the depth of the heating layer was larger than the cut depth, the surface roughness of the LAM was higher than that of the CM. Range analysis revealed that the cutting speed had the largest effect on the maximum wear depth of the rake face. Based on linear regression analysis, the cutting depth had a larger effect on the surface roughness in LAM. The average error between the linear regression prediction equation and the experimental results for surface roughness was 4.30%.
引用
收藏
页数:17
相关论文
共 50 条
  • [31] Study on the effect of laser-assisted machining on tool wear based on molecular dynamics simulation
    Liu, Zaiwei
    Lin, Bin
    Liang, Xiaohu
    Du, Anyao
    DIAMOND AND RELATED MATERIALS, 2020, 109
  • [32] Laser-assisted High Speed Machining of Aluminium Alloy: The Effect of Ultrasonic-induced Droplet Vegetable-based Cutting Fluid on Surface Roughness and Tool Wear
    Yasmin, F.
    Tamrin, K. F.
    Sheikh, N. A.
    LASERS IN ENGINEERING, 2021, 48 (4-6) : 195 - 225
  • [33] Surface Roughness and Tool Wear on Cryogenic Treated CBN Insert on Titanium and Inconel 718 Alloy Steel
    Thamizhmanii, S.
    Mohideen, R.
    Zaidi, A. M. A.
    Hasan, S.
    3RD INTERNATIONAL CONFERENCE OF MECHANICAL ENGINEERING RESEARCH (ICMER 2015), 2015, 100
  • [34] Analysis of cryogenic tool wear during electrical discharge machining of titanium alloy grade 5
    Choudhary, Rajesh
    Kumar, Amar
    Yadav, Gyanendra
    Yadav, Rammurat
    Kumar, Vikas
    Akhtar, Javed
    MATERIALS TODAY-PROCEEDINGS, 2020, 26 : 864 - 870
  • [35] Prediction of surface roughness of titanium alloy in abrasive waterjet machining process
    Ting, Ho Yi
    Asmelash, Mebrahitom
    Azhari, Azmir
    Alemu, Tamiru
    Saptaji, Kushendarsyah
    INTERNATIONAL JOURNAL OF INTERACTIVE DESIGN AND MANUFACTURING - IJIDEM, 2022, 16 (01): : 281 - 289
  • [36] Tool Quality Life during Ball End Milling of Titanium Alloy Based on Tool Wear and Surface Roughness Models
    Zhao, Zemin
    Liu, Xianli
    Yue, Caixu
    Li, Rongyi
    Zhang, Hongyan
    Liang, Steven
    APPLIED SCIENCES-BASEL, 2020, 10 (09):
  • [37] Prediction of surface roughness of titanium alloy in abrasive waterjet machining process
    Ho Yi Ting
    Mebrahitom Asmelash
    Azmir Azhari
    Tamiru Alemu
    Kushendarsyah Saptaji
    International Journal on Interactive Design and Manufacturing (IJIDeM), 2022, 16 : 281 - 289
  • [38] Comprehensive analysis of tool wear, tool life, surface roughness, costing and carbon emissions in turning Ti-6Al-4V titanium alloy: Cryogenic versus wet machining
    Agrawal, Chetan
    Wadhwa, Jwalant
    Pitroda, Anjali
    Pruncu, Catalin Iulian
    Sarikaya, Murat
    Khanna, Navneet
    TRIBOLOGY INTERNATIONAL, 2021, 153
  • [39] Numerical modeling of laser assisted machining of a beta titanium alloy
    Xi, Yao
    Zhan, Hongyi
    Rashid, R. A. Rahman
    Wang, Gui
    Sun, Shoujin
    Dargusch, Matthew
    COMPUTATIONAL MATERIALS SCIENCE, 2014, 92 : 149 - 156
  • [40] Experimental Investigation and Optimizing of Turning Parameters for Machining of Al7075-T6 Aerospace Alloy for Reducing the Tool Wear and Surface Roughness
    Singh, Jasjeevan
    Gill, Simranpreet Singh
    Mahajan, Amit
    JOURNAL OF MATERIALS ENGINEERING AND PERFORMANCE, 2023, 33 (17) : 8745 - 8756