Wear Progress Prediction of Carbide Tool in Turning of AISI1045 by Using FEM

  • L.-J. Xie
  • C. Schmidt
  • F. Biesinger
  • J. Schmidt
  • S.-Q. Pang
Conference paper

Abstract

FEM is a powerful tool for predicting cutting process variables, which are difficult to obtain with experimental methods. In this paper modeling techniques on continuous chip formation using the commercial FEM code ABAQUS are discussed. A combination of three chip formation analysis steps including initial chip formation, chip growth and steady-state chip formation is used to simulate the continuous chip formation process. Furthermore, after introducing a heat transfer analysis, temperature distribution of the cutting insert at steady state is obtained. In this way, cutting process variables e.g. contact pressure (normal stress) at tool/chip and tool/work interface, relative sliding velocity and cutting temperature distribution at steady state are predicted. Many researches show that tool wear rate is dependent on these cutting process variables and their relationship is described by some wear rate models. By implementing a Python-based tool wear estimate program, that launches chip formation and heat transfer analysis, reads predicted cutting process variables, calculates tool wear based on wear rate model and then updates tool geometry, tool wear progress in turning operation is estimated. In addition, the predicted crater wear and flank wear are verified with experimental results.

Keywords

Tool wear FEM Turning operation Chip formation Orthogonal cutting 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    Usui, E., Shirakashi, T. and Kitagawa, T., 1978, “Analytical prediction of three dimensional cutting process, part 3: cutting temperature and crater wear of carbide tool”, Journal of Engineering for Industry, 100 (5), pp.236–243.Google Scholar
  2. [2]
    Kitagawa, T., Maekawa, M., Shirakashi, T. and Usui, E., 1989, “Analytical prediction of flank wear of carbide tools in turning plain carbon steels, part 2: prediction of flank wear”, Bull. Japan Soc. of Prec. Engg, 23 (2), pp.126–133.Google Scholar
  3. [3]
    Yen, Y. C., Söhner, J., Weule, H., Schmidt, J. and Altan, T., 2002, “Estimation of tool wear of carbide tool in orthogonal cutting using FEM simulation”, Proceedings of the 5th CIRP International Workshop on Modeling of Machining Operations, pp.149–160.Google Scholar
  4. [4]
    HSK Inc., 2001, ABAQUS Scripting Manual Version 6.2, U.S.A.Google Scholar
  5. [5]
    Schulze V, Vöhringer O., 2000, “Influence of alloying elements on the strain rate and temperature dependence of the flow stress of steels”, Metallurgical and Materials Transactions A, 31A.Google Scholar
  6. [6]
    HSK Inc., 2001, ABAQUS/Explicit User’s Manual Version 6.2, U.S.A.Google Scholar
  7. [7]
    Xie, L. J., 2003, Estimation of two-dimension tool wear based on finite element method, Dissertation, Universität Karlsruhe (TH).Google Scholar
  8. [8]
    HSK Inc., 2001, ABAQUS/Standard User’s Manual Version 6.2, U.S.A.Google Scholar
  9. [9]
    Kitagawa, T., Maekawa, K., Shirakashi, T. and Usui, E., 1988, “Analytical prediction of flank wear of carbide tools in turning plain carbon steels, part 1: characteristic equation of flank wear”, Bull. Japan Soc. of Prec. Engg, 22 (4), pp.263–269.Google Scholar
  10. [10]
    Schmidt, C., 2002, “Development of a FEM-based tool wear model to estimate tool wear and tool life in metal cutting”, Diplomarbeit, Universität Karlsruhe (TH).Google Scholar

Copyright information

© Tsinghua University Press, Beijing and Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • L.-J. Xie
    • 1
  • C. Schmidt
    • 2
  • F. Biesinger
    • 3
  • J. Schmidt
    • 2
  • S.-Q. Pang
    • 1
  1. 1.School of Mechanical and Vehicular EngineeringBeijing Institute of TechnologyBeijingChina
  2. 2.Institut für Produktionstechnik (wbk)Universität Karlsruhe(TH)Germany
  3. 3.Institut für Werkstoffkunde IUniversität Karlsruhe(TH)Germany

Personalised recommendations