International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Selection of Parameters for Electro-Chemical Machining (ECM) using Genetic Algorithm

Abstract

The parameters influence the metal removal rate of any process. The selection of parameters plays a vital role in the process. Therefore, the selection of optimum parameters for electrochemical machining (ECM) is illustrated in this paper. The optimization problem is formulated with the maximization of the material removal rate (MRR) and optimum parameters i.e. electrolyte concentration (C), flow rate (Q), applied voltage (V), and feed rate (f) are considered as design variables. The formulated optimization problem is solved using Genetic Algorithm (GA). GA algorithm is coded in MATLAB.  Optimum parameters are applied to obtain maximum MRR for ECM process.

Country : India

1 Prem Singh2 Trivendra Kumar Sharma3 Md. Suhaib4 Sunil Kumar

  1. Department of Mechanical Engineering, Swami Keshvanand Institute of Technology, Management & Gramothan, Jaipur, Rajasthan, India
  2. Department of Mechanical Engineering, Swami Keshvanand Institute of Technology, Management & Gramothan, Jaipur, Rajasthan, India
  3. Department of Mechanical Engineering, Swami Keshvanand Institute of Technology, Management & Gramothan, Jaipur, Rajasthan, India
  4. Department of Mechanical Engineering, Swami Keshvanand Institute of Technology, Management & Gramothan, Jaipur, Rajasthan, India

IRJIET, Volume 7, Issue 4, April 2023 pp. 7-10

doi.org/10.47001/IRJIET/2023.704002

Full Paper
Download

References

  1. Z. Zhang, D. Zhu, N. Qu, and M. Wang, “Theoretical and experimental investigation on electrochemical micromachining,” Microsyst. Technol., vol. 13, no. 7, pp. 607–612, 2007, doi: 10.1007/s00542-006-0369-7.
  2. K. P. Rajurkar, D. Zhu, J. A. McGeough, J. Kozak, and A. De Silva, “New developments in electro-chemical machining,” CIRP Ann. - Manuf. Technol., vol. 48, no. 2, pp. 567–579, 1999, doi: 10.1016/S0007-8506(07)63235-1.
  3. K. Raja and R. Ravikumar, “A review on electrochemical machining processes,” International Journal of Applied Engineering Research, vol. 11, no. 4. pp. 2354–2355, 2016.
  4. R. V. Rao, P. J. Pawar, and R. Shankar, “Multi-objective optimization of electrochemical machining process parameters using a particle swarm optimization algorithm,” Proc. Inst. Mech. Eng. Part B J. Eng. Manuf., vol. 222, no. 8, pp. 949–958, 2008, doi: 10.1243/09544054JEM1158.
  5. P. Asokan, R. R. Kumar, R. Jeyapaul, and M. Santhi, “Development of multi-objective optimization models for electrochemical machining process,” Int. J. Adv. Manuf. Technol., vol. 39, no. 1–2, pp. 55–63, 2008, doi: 10.1007/s00170-007-1204-8.
  6. J. Munda and B. Bhattacharyya, “Investigation into electrochemical micromachining (EMM) through response surface methodology-based approach,” Int. J. Adv. Manuf. Technol., vol. 35, no. 7–8, pp. 821–832, 2008, doi: 10.1007/s00170-006-0759-0.
  7. A.Bhattacharyya, B. Sur, and S. K. Sorkhel, “Analysis of optimum parametric combination in electro-chemical machining,” Ann. CIRP, vol. 22, pp. 59–60, 1973.
  8. El-Dardery and M. A., “Economic study of electro- chemical machining,” Int. J. Mach. Tool Des. Res., vol. 22, pp. 147–158, 1982.
  9. M. HEWIDY, M. FATTOUH, and M. ELKHABEERY, “SOME ECONOMICAL ASPECTS OF ECM PROCESSES,” Int. Conf. Appl. Mech. Mech. Eng., vol. 1, no. 1, pp. 87–94, 1984, doi: 10.21608/amme.1984.49203.
  10. M. S. Hewidy, S. J. Ebeid, T. A. El-Taweel, and A. H. Youssef, “Modelling the performance of ECM assisted by low frequency vibrations,” J. Mater. Process. Technol., vol. 189, no. 1–3, pp. 466–472, 2007, doi: 10.1016/j.jmatprotec.2007.02.032.
  11. C. Senthilkumar, G. Ganesan, and R. Karthikeyan, “Parametric optimization of electrochemical machining of Al/15 SiC p composites using NSGA-II,” Trans. Nonferrous Met. Soc. China (English Ed., vol. 21, no. 10, pp. 2294–2300, 2011, doi: 10.1016/S1003-6326(11)61010-8.
  12. P. Singh and H. Chaudhary, “Optimum two-plane balancing of rigid rotor using discrete optimization algorithm,” World J. Eng., vol. 16, no. 1, pp. 138–146, 2019, doi: 10.1108/WJE-05-2018-0167.
  13. Dastanpour, Amin and Raja Mahmood, "Feature Selection Based on Genetic Algorithm and Support Vector Machine for Intrusion Detection System,' 2013, doi  - 10.13140/2.1.4289.4721

Copyright @ 2026-2017 IRJIET. All Right Reserved.

Developed by Byzero Technologies