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Parametric Optimization of Electrochemical Machining Process Using Taguchi Method and Super Ranking Concept While Machining on Inconel 825

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Advanced Engineering Optimization Through Intelligent Techniques

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 949))

Abstract

To exploit the fullest machining potential of electrochemical machining (ECM) process while machining on Inconel 825, it is recommended to operate the machine with the optimal combination of machining process parameters. Past researchers have already applied grey relational analysis (GRA) as an optimization tool so as to obtain the optimal parametric combination of ECM process. In this paper, based on the experimental data obtained by the past researchers, Taguchi method and super ranking concept is applied to analyze the efficacy of the proposed approach in obtaining the optimal parametric combination of ECM process. The derived parametric combination is validated with respect to the predicted response values, obtained from the developed regression equations which show that the proposed approach results in improved response values than that obtained by past researchers. Finally, Analysis of variance (ANOVA) is applied to identify the influence of each process parameters for the considered ECM process.

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References

  1. El-Hofy, H.: Advanced Machining Processes: Nontraditional and Hybrid Machining Processes. McGraw-Hill, New York (2005)

    Google Scholar 

  2. Jain, N.K., Jain, V.K.: Optimization of electro-chemical machining process parameters using genetic algorithms. Mach. Sci. Technol. 11(2), 235–258 (2007)

    Article  Google Scholar 

  3. Asokan, P., Kumar, R.R., Jeyapaul, R., Santhi, M.: Development of multi-objective optimization models for electrochemical machining process. Int. J. Adv. Manuf. Technol. 39(1–2), 55–63 (2008)

    Article  Google Scholar 

  4. Rao, R., Yadava, V.: Multi-objective optimization of Nd: YAG laser cutting of thin superalloy sheet using grey relational analysis with entropy measurement. Opt. Laser Technol. 41(8), 922–930 (2009)

    Article  Google Scholar 

  5. Mukherjee, R., Chakraborty, S.: Selection of the optimal electrochemical machining process parameters using biogeography-based optimization algorithm. Int. J. Adv. Manuf. Technol. 64(5–8), 781–791 (2013)

    Article  Google Scholar 

  6. Tang, L., Yang, S.: Experimental investigation on the electrochemical machining of 00Cr12Ni9Mo4Cu2 material and multi-objective parameters optimization. Int. J. Adv. Manuf. Technol. 67(9–12), 2909–2916 (2013)

    Article  Google Scholar 

  7. Lal, S., Kumar, S., Khan, Z.A., Siddiquee, A.N.: Multi-response optimization of wire electrical discharge machining process parameters for Al7075/Al2O3/SiC hybrid composite using Taguchi-based grey relational analysis. Proc. Inst. Mech. Eng. B: J. Eng. Manuf. 229(2), 229–237 (2015)

    Article  Google Scholar 

  8. Bose, G.K.: Multi objective optimization of ECG process under fuzzy environment. Multidiscip. Model. Mater. Struct. 11(3), 350–371 (2015)

    Article  Google Scholar 

  9. Rao, S.R., Padmanabhan, G.: Parametric optimization in electrochemical machining using utility based Taguchi method. Int. J. Eng. Sci. Technol. 10(1), 81–96 (2015)

    Google Scholar 

  10. Mehrvar, A., Basti, A., Jamali, A.: Optimization of electrochemical machining process parameters: combining response surface methodology and differential evolution algorithm. Proc. Inst. Mech. Eng. E: J. Proc. Mech. Eng. 231(6), 1114–1126 (2017)

    Article  Google Scholar 

  11. Rahang, M., Patowari, P.K.: Parametric optimization for selective surface modification in EDM using Taguchi analysis. Mater. Manuf. Processes 31(4), 422–431 (2016)

    Article  Google Scholar 

  12. Dhuria, G.K., Singh, R., Batish, A.: Application of a hybrid Taguchi-entropy weight-based GRA method to optimize and neural network approach to predict the machining responses in ultrasonic machining of Ti–6Al–4V. J. Braz. Soc. Mech. Sci. Eng. 39(7), 2619–2634 (2017)

    Article  Google Scholar 

  13. Antil, P., Singh, S., Manna, A.: Electrochemical discharge drilling of SiC reinforced polymer matrix composite using Taguchi’s grey relational analysis. Arab. J. Sci. Eng. 43(3), 1257–1266 (2018)

    Article  Google Scholar 

  14. Cole, K.M., Kirk, D.W., Singh, C.V., Thorpe, S.J.: Optimizing electrochemical micromachining parameters for Zr-based bulk metallic glass. J. Manuf. Processes. 25, 227–234 (2017)

    Article  Google Scholar 

  15. Manikandan, N., Kumanan, S., Sathiyanarayanan, C.: Multiple performance optimization of electrochemical drilling of Inconel 625 using Taguchi based grey relational analysis. Eng. Sci. Technol. Int. J. 20(2), 662–671 (2017)

    Article  Google Scholar 

  16. Chakraborty, S., Das, P.P., Kumar, V.: Application of grey-fuzzy logic technique for parametric optimization of non-traditional machining processes. Grey Syst.: Theory Appl. 8(1), 46–68 (2018)

    Article  Google Scholar 

  17. Taddese, F.: Parameter optimization of ECH process for surface finish on ASTM-35 cast iron. Int. J. Adv. Manuf. Technol. 1–12 (2018)

    Google Scholar 

  18. Chakraborty, S., Das, P.P.: A multivariate quality loss function approach for parametric optimization of non-traditional machining processes. Manag. Sci. Lett. 8(8), 873–884 (2018)

    Article  Google Scholar 

  19. Taguchi, G.: Introduction to quality engineering: designing quality into products and processes (No. 658.562 T3) (1986)

    Google Scholar 

  20. Taguchi, G., Konishi, S.: Taguchi methods: Orthogonal arrays and linear graphs: tools for quality engineering, Amer. Suppl. Inst. (1987)

    Google Scholar 

  21. Besseris, G.J.: Multi-response optimisation using Taguchi method and super ranking concept. J. Manuf. Technol. Manag. 19(8), 1015–1029 (2008)

    Article  Google Scholar 

  22. Nayak, A.A., Gangopadhyay, S., Sahoo, D.K.: Modelling, simulation and experimental investigation for generating ‘I’shaped contour on Inconel 825 using electro chemical machining. J. Manuf. Processes. 23, 269–277 (2016)

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Mechanical Engineering, Sikkim Manipal Institute of Technology, Sikkim Manipal University, Majitar, Sikkim, India

    Partha Protim Das

  2. Department of Production Engineering, Jadavpur University, Kolkata, West Bengal, India

    Shankar Chakraborty

Authors
  1. Partha Protim Das
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  2. Shankar Chakraborty
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Corresponding author

Correspondence to Partha Protim Das .

Editor information

Editors and Affiliations

  1. Sardar Vallabhbhai National Institute of Technology, Surat, Surat, Gujarat, India

    R. Venkata Rao

  2. Cracow University of Technology, Kraków, Poland

    Jan Taler

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Das, P.P., Chakraborty, S. (2020). Parametric Optimization of Electrochemical Machining Process Using Taguchi Method and Super Ranking Concept While Machining on Inconel 825. In: Venkata Rao, R., Taler, J. (eds) Advanced Engineering Optimization Through Intelligent Techniques. Advances in Intelligent Systems and Computing, vol 949. Springer, Singapore. https://doi.org/10.1007/978-981-13-8196-6_36

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