Skip to main content
SpringerLink
Log in

Optimal Process Design in Hot Forging in Terms of Grain Flow Quality

  • Published:
International Journal of Automotive Technology Aims and scope Submit manuscript

Abstract

With the improvement in the accuracy of simulation and computation time, the need for the application of optimization technique in designing process parameters is increasing and is being realized in some fields. However, two obstacles are still preventing the optimization technique from being practically used in forging process. The one is the lack of quantification technique of grain flow quality and the other is difficulty in treating 3 dimensional die shape as design parameters. In this study, 3 kinds of quantification technique of grain flow quality, the overlapping index, cutting index and locally sinking index, are introduced based on the relation between grain flow and product quality. Also, a methodology of treating 3 dimensional die shape as the design parameters is introduced using discretized finite element model.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Abbreviations

x i :

axis

δ ij :

Kronecker delta

\(G_{{\rm{pq}}}^{\rm{i}}\) :

gradient of grain flow density

\(\overline {{G^1}}\) :

overlapping index

ψ 0 :

objective function

ϕ i :

grain flow function

n :

outward directed unit normal vector

F max :

maximum forming load, kN

\(\overline \varepsilon\) :

effective strain

b i :

design variable

\(\overrightarrow {{n_0}}\) :

rotational axis vector of cylinder

R:

radius, mm

C, P:

critical points defining geometry

\(\overrightarrow {{n_1}} ,\,\overrightarrow {{t_1}}\) :

directional vector between critical points

θ :

angle, radian

S i :

distance between critical points

t ij :

j-th component of i-th directional vector

References

  • Badrinarayanan, S. and Zabaras, N. (1996). A sensitivity analysis for the optimal design of metal-forming processes. Computer Methods in Applied Mechanics and Engineering 129, 4, 319–348.

    Article  Google Scholar 

  • Choi, M. H. (2015). Study on Metal Forming Process Design for Bearing Parts with Emphasis on Metal Flow Lines. Ph. D. Dissertation. Gyeongsang National University. Jinju, Korea.

    Google Scholar 

  • Chung, S. H. and Hwang, S. M. (1998a). Optimal process design in non-isothermal non-steady metal forming by the finite element method. Int. J. Numerical Methods in Engineering 42, 8, 1343–1390.

    Article  Google Scholar 

  • Chung, S. H. and Hwang, S. M. (1998b). Application of a genetic algorithm to process optimal design in non-isothermal metal forming. J. Materials Processing Technology, 80–81, 136–143.

    Article  Google Scholar 

  • Chung, S. H. and Hwang, S. M. (2002). Process optimal design in forging by genetic algorithm. J. Manufacturing Science and Engineering 124, 2, 397–408.

    Article  Google Scholar 

  • Equbal, I. M., Kumar, R., Shamin, M. and Ohdar, R. K. (2014). A grey-based Taguchi method to optimize hot forging process. Procedia Materials Science, 6, 1495–1504.

    Article  Google Scholar 

  • Fourment, L. and Chenot, J. L. (1996). Optimal design for non-steady-state metal forming processes — I. Shape optimization method. Int. J. Numerical Methods in Engineering 39, 1, 33–50.

    Article  Google Scholar 

  • Fourment, L., Balan, T. and Chenot, J. L. (1996). Optimal design for non-steady-state metal forming processes — II. Application of shape optimization in forging. Int. J. Numerical Methods in Engineering 39, 1, 51–65.

    Article  Google Scholar 

  • Guan, Y., Bai, X., Liu, M., Song, L. and Zhao, G. (2014). 3D preform design in forging process based on quasi-quipotential field and response surface methods. Procedia Engineering, 81, 468–473.

    Article  Google Scholar 

  • Hashemzadeh, H., Eftekhari, S. A. and Loh-Mousavi, M. (2017). Forging pre-form dies optimization using artificial neural networks and continuous genetic algorithm. Bioscience Biotechnology Research Communications, 1, 74–86.

    Google Scholar 

  • Huda, Z. (2012). Reengineering of manufacturing process design for quality assurance in axle-hubs of a modern car — A case study. Int. J. Automotive Technology 13, 7, 1113–1118.

    Article  Google Scholar 

  • Joun, M. S. and Hwang, S. M. (1993a). Optimal process design in steady-state metal forming by finite element method — I. Theoretical considerations. Int. J. Machine Tools and Manufacture 33, 1, 51–61.

    Article  Google Scholar 

  • Joun, M. S. and Hwang, S. M. (1993b). Optimal process design in steady-state metal forming by finite element method — II. Application to die profile design in extrusion. Int. J. Machine Tools and Manufacture 33, 1, 63–70.

    Article  Google Scholar 

  • Joun, M. S. and Hwang, S. M. (1993c). Pass schedule optimal design in multi-pass extrusion and drawing by finite element method. Int. J. Machine Tools and Manufacture 33, 5, 713–724.

    Article  Google Scholar 

  • Joun, M. S. and Hwang, S. M. (1998). Die shape optimal design in three-dimensional shape metal extrusion by the finite element method. Int. J. Numerical Methods in Engineering 41, 2, 311–335.

    Article  Google Scholar 

  • Joun, M. S. and Lee, M. C. (2017). Quality of grain flow of metal formed products. Proc. Conf. Korean Society for Technology of Plasticity, 53–54.

  • Joun, M. S., Moon, H. K. and Shivpuri, R. (1998). Automatic simulation of a sequence of hot-former forging processes by a rigid-thermoviscoplastic finite element method. J. Engineering Materials and Technology 120, 4, 291–296.

    Article  Google Scholar 

  • Kim, M. C., Chung, S. H. and Joun, M. S. (2017). A study on optimization of die shape parameters of a forging process. Proc. Conf. Korean Society for Technology of Plasticity, 199–200.

  • Ko, D. C., Kim, D. H. and Kim, B. M. (1999). Application of artificial neural network and Taguchi method to preform design in metal forming considering workability. Int. J. Machine Tools and Manufacture 39, 5, 771–785.

    Article  Google Scholar 

  • Kim, M. C., Chung, S. H. and Joun, M. S. (2018). Optimal process design of hot forging processes in terms of grain flow quality. Proc. AEPA2018, Jeju, Korea.

  • Lee, C. H. and Kobayashi, S. (1973). New solutions to rigid-plastic deformation problems using a matrix method. J. Engineering for Industry 95, 3, 865–763.

    Article  Google Scholar 

  • Lee, J. J., Jung, U. J. and Park, G. J. (2013). Shape optimization of the workpiece in the forming process using equivalent static loads. Finite Elements in Analysis and Design, 69, 1–18.

    Article  Google Scholar 

  • Lu, B., Ou, H., Armstrong, C. G. and Rennie, A. (2009). 3D die shape optimization for net-shape forging of aerofoil blades. Materials & Design 30, 7, 2490–2500.

    Article  Google Scholar 

  • Marinković, V. and Janković, P. (2017). Application of regression method for determining the die land dimensions based on data from industry. FME Trans., 45, 590–596.

    Article  Google Scholar 

  • Mirahmadi, S. J. and Hamedi, M. (2017). Flash gap optimization in precision blade forging. Int. J. Mechanical Engineering and Robotics Research 6, 3, 200–205.

    Article  Google Scholar 

  • Moon, H. K., Kim, M. C. and Joun, M. S. (2018). Optimal design of forging process of the first generation hub bearing outer race considering the symmetry of metal flow lines. Proc. Conf. Korean Society for Technology of Plasticity, 24–25.

  • Moon, H. K., Lee, J. S., Yoo, S. J., Joun, M. S. and Lee, J. K. (2007). Hot deformation behavior of bearing steels. J. Engineering Materials and Technology 129, 3, 349–355.

    Article  Google Scholar 

  • Moon, H. K., Moon, S. C., Eom, J. G. and Joun, M. S. (2005). Optimization of a hot forging process using six sigma scheme and computer simulation technology considering required metal flow lines. Trans. Materials Processing 14, 9, 798–803.

    Article  Google Scholar 

  • Ozturk, M., Kocaoglan, S. and Sonmez, F. O. (2016). Concurrent design and process optimization of forging. Computers & Structures, 167, 24–36.

    Article  Google Scholar 

  • Pajot (2013). https://blog.altair.com/hyperstudy-global-response-surface-method-grsm

  • Pietrzyk, M., Madej, L. and Weglarczyk, S. (2008). Tool for optimal design of manufacturing chain based on metal forming. CIRP Annals 57, 1, 309–312.

    Article  Google Scholar 

  • Roy, S., Ghosh, S. and Shivpuri, R. (1997). A new approach to optimal design of multi-stage metal forming processes with micro genetic algorithms. Int. J. Machine Tools and Manufacture 37, 1, 29–44.

    Article  Google Scholar 

  • Shao, Y., Lu, B., Xu, D. K., Chen, J., Ou, H., Long, H. and Guo, P. Y. (2016). Topology-based preform design optimization for blade forging. Int. J. Advanced Manufacturing Technology 86, 5–8, 1593–1605.

    Article  Google Scholar 

  • Zhao, G., Ma, X., Zhao, X. and Grandhi, R. V. (2004). Studies on optimization of metal forming processes using sensitivity analysis methods. J. Materials Processing Technology 147, 2, 217–228.

    Article  Google Scholar 

  • Zienkiewicz, O. C. (1977). The Finite Element Method. 3rd edn. McGraw-Hill. London, UK.

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Mechanical Engineering, Gyeongsang Nation University, Gyeongnam, 52828, Korea

    Min Cheol Kim & Man Soo Joun

  2. R&D Team, MFRC, 5 Nonhyeon-ro 64-gil, Gangnam-gu, Seoul, 06228, Korea

    Suk Hwan Chung

Authors
  1. Min Cheol Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Suk Hwan Chung
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Man Soo Joun
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Man Soo Joun.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This paper was significantly extended and modified from the original paper presented in Asia-Pacific Symposium on Engineering Plasticity and its Applications 2018, and recommended by the Scientific & Technical Committee for journal publication.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kim, M.C., Chung, S.H. & Joun, M.S. Optimal Process Design in Hot Forging in Terms of Grain Flow Quality. Int.J Automot. Technol. 20 (Suppl 1), 45–56 (2019). https://doi.org/10.1007/s12239-019-0127-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12239-019-0127-3

Key Words

Search

Navigation