Workpiece material model based predictions for machining processes

被引:0
|
作者
Karpat, Y [1 ]
Zeren, E [1 ]
Özel, T [1 ]
机构
[1] Rutgers State Univ, Dept Syst & Ind Engn, Piscataway, NJ 08854 USA
关键词
heat source method; cutting forces; temperature distributions;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In this paper, a methodology for work material constitutive model based calculations of forces, stress and temperature distributions in orthogonal machining are introduced. Oblique moving band heat source theory is utilized and combined with modified Oxley's parallel shear zone theory. Non-uniform heat intensity at the tool-chip interface is obtained from the predicted stress distributions utilizing slip line analysis of the modified secondary shear zone. Model validation is performed by comparing some experimental results with the predictions for machining of AISI 1045 steel and AL 6082-T6. Good agreements with the experiments are observed. A detailed stress and temperature distributions computed analytically is obtained.
引用
收藏
页码:413 / 420
页数:8
相关论文
共 50 条
  • [1] The Workpiece Material in Machining
    J. H. Dautzenberg
    S. P. F. C. Jaspers
    D. A. Taminiau
    [J]. The International Journal of Advanced Manufacturing Technology, 1999, 15 : 383 - 386
  • [2] The workpiece material in machining
    Dautzenberg, JH
    Jaspers, SPFC
    Taminiau, DA
    [J]. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 1999, 15 (06): : 383 - 386
  • [3] Predictive model for workpiece surface error due to machining processes
    General Motors Corporation, Pontiac, MI, United States
    [J]. Tech Pap Soc Manuf Eng MR, MR99-247 (1-12):
  • [4] Bayesian Learning-Based Model-Predictive Vibration Control for Thin-Walled Workpiece Machining Processes
    Yuan, Ye
    Zhang, Hai-Tao
    Wu, Yue
    Zhu, Tao
    Ding, Han
    [J]. IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2017, 22 (01) : 509 - 520
  • [5] FE-simulation of machining processes with a new material model
    Buchkremer, S.
    Wu, B.
    Lung, D.
    Muenstermann, S.
    Klocke, F.
    Bleck, W.
    [J]. JOURNAL OF MATERIALS PROCESSING TECHNOLOGY, 2014, 214 (03) : 599 - 611
  • [6] Explainable AI based Predictions for Workpiece Quality
    Straub, Timm
    Guckert, Michael
    Fiedler, Udo
    Strauch, Simon
    [J]. e-Journal of Nondestructive Testing, 2024, 29 (10):
  • [7] Model of workpiece erosion for electrical discharge machining process
    Sharakhovsky, Leonid I.
    Marotta, Aruy
    Essiptchouk, Alexei M.
    [J]. APPLIED SURFACE SCIENCE, 2006, 253 (02) : 797 - 804
  • [8] Material wear of the tool electrode and metal workpiece in electrochemical discharge machining
    Islam, Mohammad Jahedol
    Zhang, Yan
    Zhao, Liang
    Yang, Wentao
    Bian, Haowen
    [J]. Wear, 2022, 500-501
  • [9] A novel technique for identifying unknown workpiece material through machining/turning
    Huda, Zainul
    [J]. MATERIALS AND MANUFACTURING PROCESSES, 2023, 38 (06) : 747 - 754
  • [10] Material wear of the tool electrode and metal workpiece in electrochemical discharge machining
    Islam, Mohammad Jahedol
    Zhang, Yan
    Zhao, Liang
    Yang, Wentao
    Bian, Haowen
    [J]. WEAR, 2022, 500