Effect of process variables on surface roughness in electrochemical machining of stainless steel 304

  • Authors

    • Abbas Fadhil Ibrahim Metallurgical and Production Engineering Department, University of Technology/Baghdad
    • Mostafa Adel Abdullah Metallurgical and Production Engineering Department, University of Technology/Baghdad
    • Safaa Kadhim Ghazi Metallurgical and Production Engineering Department, University of Technology/Baghdad
    • O. H. Hassoon Metallurgical and Production Engineering Department, University of Technology/Baghdad
    2019-07-14
    https://doi.org/10.14419/ijet.v7i4.28885
  • ECM, RA, Response Surface Methodology, Stainless Steel.
  • The electrochemical machining process is largely used in industry operations to manufacture components used in automotive, aerospace and medical applications. The optimal conditions of this process can significant reducing the electrochemical machining operating, maintenance cost, tooling, and producing of components with high accuracy. The more requirements of the processes are that work piece must be electrical conduct. Due to various independent variables in this process, difficulties are presented in the chosen and analysis of the experimental results. In this work, the response surface methodology and analysis of variance method are applied to optimize ECM process and to study the more effective parameters (current, inter- electrode gap, and concentration of electrolyte) on surface roughness of stainless steel 304 workpiece. An empirical equation formula is proposed based on the experimental results and the statistical model that used to predict the surface roughness. The R2 (ability the Input variables to prediction the output variables) of the predictive model was 92.6%. The experimental results were shown that the current considered the most effective factor to minimize the Ra, while the electrolyte concentration considered the second affect factor.

     

  • References

    1. [1] D. Zhu, D. Xu, Q. Xu and J. Liu, " Investigation on the flow field of W-shape electrolyte flow mode in electrochemical machining", Journal of Applied Chemistry, vol. 40. pp. 525-532, 2010. https://doi.org/10.1007/s10800-009-0024-y.

      [2] K. Mishra, D. Dey, B.R. Sarkar and B. Bhattacharyya, "Experimental investigation into electrochemical milling of Ti6Al4V", Journal of Manufacturing Processes, vol. 29. pp. 113-123, 2017. https://doi.org/10.1016/j.jmapro.2017.07.014.

      [3] P.V. Jadhav and D.S. Bilgi, "Sumit Sharan, Rachit Shrivastava, Experimental Investigation on MRR of Pulse Electrochemical machining (PECM) based on Taguchi Method", International Journal of Innovative Research in Science Engineering and Technology, vol. 3. pp. 8800-8809, 2014.

      [4] H.K. Kansal, S. Sehijpa, and P. Kumar, " Parametric optimization of powder mixed electrical discharge machining by response surface methodology", Journal of Material Processing Technology, vol.169. pp. 427-436, 2005. https://doi.org/10.1016/j.jmatprotec.2005.03.028.

      [5] D. Kanagarajan, R. Karthikeyan, and K. Palanikumar, "Parametric optimization of electro discharge machining characteristics of WC/Co composites by response surface methodology", Journal of Engineering Manufacture, pp. 222: 807-815, 2007. https://doi.org/10.1243/09544054JEM925.

      [6] N.K. Jain and V.K. jain, "Optimzation of electrochemical machining process parameters using genetic algorithm", Machining Science and Technology, vol.11. pp. 235-258, 2007. https://doi.org/10.1080/10910340701350108.

      [7] P. Asokan, R. Ravi Kumar, R. Jeyapoul and M. Sarhi, "Development of multi- objective optimization models for electrochemical machining process", International Journal of Advanced ManufacturingTechnology, vol. 39. pp. 55-63, 2008. https://doi.org/10.1007/s00170-007-1204-8.

      [8] D. Chakradhar and A. Venu Gopal, "Multi-objective optimization of electrochemical machining of EN31 steel by grey relational analysis", International Journal of modeling and optimization, vol. 1. pp. 113-117, 2011. https://doi.org/10.7763/IJMO.2011.V1.20.

      [9] Abbas Fadhil Ibrahim, "Prediction of Surface Roughness and Material Removal Rate in Electrochemical Machining Using Taguchi Method", Al-Khwarizmi Engineering Journal, vol. 12. pp. 72-80, 2016. https://doi.org/10.22153/kej.2016.06.001.

      [10] S. Abhijith, P. Srinivasa Pai, Bhaskara Achar and Grynal D’mello, “Multi-objective optimization and modeling of surface roughness in inconel 718 using Taguchi grey relational analysis and response surface methodologyâ€, International Journal of Engineering & Technology, vol. 7. pp. 724-728, 2018.

      [11] C. Senthilkumar, G. Ganesan, and R. Karthikeyan, "Influence of Input Parameters on Characteristics of Electro Chemical Machining Process", International Journal of Applied Science and Engineering, vol. 11. pp. 13-24, 2013.

      K.T. Chiang, F.P. Chang and D.C. Tsai, "Modeling and analysis of the rapidly resolidified layer of SG cast iron in the EDM process through the response surface methodology", Journal of Material Processing Technology, vol. 182. pp. 525-533, 2007. https://doi.org/10.1016/j.jmatprotec.2006.09.012
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  • How to Cite

    Fadhil Ibrahim, A., Adel Abdullah, M., Kadhim Ghazi, S., & H. Hassoon, O. (2019). Effect of process variables on surface roughness in electrochemical machining of stainless steel 304. International Journal of Engineering & Technology, 7(4), 6899-6901. https://doi.org/10.14419/ijet.v7i4.28885