Journal of Computational Design and Engineering

Society for Computational Design and Engineering (한국CDE학회)
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Steel nitriding optimization through multi-objective and FEM analysis

  • Received : 2015.04.20
  • Accepted : 2015.08.10
  • Published : 2016.01.01
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Abstract

Steel nitriding is a thermo-chemical process leading to surface hardening and improvement in fatigue properties. The process is strongly influenced by many different variables such as steel composition, nitrogen potential, temperature, time, and quenching media. In the present study, the influence of such parameters affecting physic-chemical and mechanical properties of nitride steels was evaluated. The aim was to streamline the process by numerical-experimental analysis allowing defining the optimal conditions for the success of the process. Input parameters-output results correlations were calculated through the employment of a multi-objective optimization software, modeFRONTIER (Esteco). The mechanical and microstructural results belonging to the nitriding process, performed with different processing conditions for various steels, are presented. The data were employed to obtain the analytical equations describing nitriding behavior as a function of nitriding parameters and steel composition. The obtained model was validated, through control designs, and optimized by taking into account physical and processing conditions.

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References

  1. Cavaliere P, Zavarise G, Perillo M. Modeling of the carburizing and nitriding processes. Computational Materials Science 2009;46(1)26-35. https://doi.org/10.1016/j.commatsci.2009.01.024
  2. Mittemeijer EJ, Somers MAJ. Thermodynamics, kinetics, and process control of nitriding. Surface Engineering 1997;13(6)483-97. https://doi.org/10.1179/sur.1997.13.6.483
  3. Appolaire B, Goune M. Linear stability analysis of a ${\gamma}'$-Fe4N nitride layer growing in pure iron. Computational Materials Science 2006;38(1)126-35. https://doi.org/10.1016/j.commatsci.2006.01.016
  4. Keddam M, Djeghlal ME, Barrallier L, Salhi E. Computer simulation of nitrided layers growth for pure iron. Computational Materials Science 2004;29(1)43-8. https://doi.org/10.1016/S0927-0256(03)00094-6
  5. Torchane L, Bilger P, Dulcy J, Gantois M. Control of iron nitride layers growth kinetics in the binary Fe-N system. Metallurgical and Materials Transactions A 1996;27A:1823-34.
  6. Dimitrov VI, D'Haen J, Knuyt G, Quaeyhaegens C, Stals LM. Modeling of nitride layer formation during plasma nitriding of iron. Computational Materials Science 1999;15(1)22-34. https://doi.org/10.1016/S0927-0256(98)00126-8
  7. Akhtar SS, Arif AFM, Yilbas BS. Evaluation of gas nitriding process with in-process variation of nitriding potential for AISI H13 tool steel. International Journal of Advanced Manufacturing Technologies 2010;47 (5-8)687-98. https://doi.org/10.1007/s00170-009-2215-4
  8. Ozdemir B, Lippmann N. Modeling and simulation of surface reactions and reactive flow of a nitriding process. Surface & Coatings Technology 2013;219:151-62. https://doi.org/10.1016/j.surfcoat.2013.01.019
  9. Peng DQ, Kim TH, Chung JH, Park JK. Development of nitride-layer of AISI 304 austenitic stainless steel during high-temperature ammonia gas-nitriding. Applied Surface Science 2010;256:7522-9. https://doi.org/10.1016/j.apsusc.2010.05.100
  10. Kong JH, Lee DJ, On HY, Park SJ, Kim SK, Kang CY, Sung JH, Lee HW. High temperature gas nitriding and tempering in 17Cr1Ni0.5C0.4V steel. Metals and Materials International 2010;16:857-63. https://doi.org/10.1007/s12540-010-1201-6
  11. Lee HW, Kong JH, Lee DJ, On HY, Sung JH. A study on high temperature gas nitriding and tempering heat treatment in 17Cr-1Ni-0.5C. Materials and Design 2009;30:1691-6. https://doi.org/10.1016/j.matdes.2008.07.023
  12. Hassani-Gangaraj SM, Guagliano M. Microstructural evolution during nitriding, finite element simulation and experimental assessment. Applied Surface Science 2013;271:156-63. https://doi.org/10.1016/j.apsusc.2013.01.154
  13. Kochmanski P, Nowacki J. Influences of initial heat treatment of 17-4 PH stainless steel on gas nitriding kinetics. Surface & Coatings Technology 2008;202:4834-8. https://doi.org/10.1016/j.surfcoat.2008.04.058
  14. Kurz SJB, Meka SR, Schell N, Ecker W, Keckes J, Mittemeijer EJ. Residual stress and microstructure depth gradients in nitrided iron-based alloys revealed by dynamical cross-sectional transmission X-ray micro-diffraction. Acta Materialia 2015;87:100-10. https://doi.org/10.1016/j.actamat.2014.12.048
  15. Keddam M, Bouarour B, Kouba R, Chegroune R. Growth kinetics of the compound layers: effect of the nitriding potential. Physics Procedia 2009;2:1399-403. https://doi.org/10.1016/j.phpro.2009.11.108
  16. Akhtar SS, Fazal A, Arif M, Yilbas BS. Influences of multiple nitriding on the case hardening of H13 tool steel: experimental and numerical investigation. International Journal of Advanced Manufacturing Tech-nology 2012;58:57-70. https://doi.org/10.1007/s00170-011-3387-2
  17. Arif AFM, Akhtar SS, Yilbas BS. Effect of process variables on gas nitriding of H13 tool steel with controlled nitriding potential. Interna-tional Journal of Surface Science and Engineering 2010;4:396-415. https://doi.org/10.1504/IJSURFSE.2010.035143
  18. Ju H, Li LX, Wang QB, Diao JP. Optimum design of the gas nitriding technological parameters of H13 steel. Gongneng Cailiao/Journal of Functional Materials 2011;42:405-7.
  19. Yang M, Zimmerman C, Donahue D, Sisson Jr. RD. Modeling the gas nitriding process of low alloy steels. Journal of Materials Engineering and Performance 2013;22:1892-8. https://doi.org/10.1007/s11665-012-0368-z
  20. Yang M, Sisson Jr. RD. Modeling the nitriding process of steels. Advanced Materials and Processes 2012;170:33-6.
  21. Williamson GK, Hall WH. X-ray line broadening from filed aluminium and wolfram. Acta Metallurgica 1953;1(1)22-31. https://doi.org/10.1016/0001-6160(53)90006-6
  22. Cavaliere P, Perrone A, Silvello A. FEM and milti-objective optimization of steel case hardening. Journal of Manufacturing Processes 2015;17: 9-27. https://doi.org/10.1016/j.jmapro.2014.10.005

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