Have a personal or library account? Click to login
Investigation and Prediction of ECMM characteristics of Hardened Die Steel with Nanoparticle Added Electrolytes Using Hybrid Deep Neural Network Cover

Investigation and Prediction of ECMM characteristics of Hardened Die Steel with Nanoparticle Added Electrolytes Using Hybrid Deep Neural Network

Open Access
|Dec 2022

References

  1. 1. Prakash, C., Kansal, H.K., Pabla, B.S. & Puri, S. (2017). Experimental investigations in powder mixed electric discharge machining of Ti–35Nb–7Ta–5Zrβ-titanium alloy. Materials and Manufacturing Processes, 32(3), 274–285. DOI: 10.1080/10426914.2016.1198018.10.1080/10426914.2016.1198018
  2. 2. Sathish, T. (2019). Experimental investigation of machined hole and optimization of machining parameters using electro-chemical machining. J. Mater. Res. Technol., 8(5), 4354–4363. DOI: 10.1016/j.jmrt.2019.07.046.10.1016/j.jmrt.2019.07.046
  3. 3. He, H.D., Qu, N.S., Zeng, Y.B. & Yao, Y.Y. (2017). Enhancement of mass transport in wire electrochemical micro-machining by using a micro-wire with surface microstructures. The International J. Adv. Manufact. Technol., 89(9), 3177–3186. DOI: 10.1007/s00170-016-9262-4.10.1007/s00170-016-9262-4
  4. 4. Sekar, T. & Marappan, R. (2008). Experimental investigations into the influencing parameters of electrochemical machining of AISI 202. J. Adv. Manufact. Systems, 7(02), 337–343. DOI: 10.1142/S0219686708001486.10.1142/S0219686708001486
  5. 5. Meng, L., Zeng, Y. & Zhu, D. (2017). Investigation on wire electrochemical micro machining of Ni-based metallic glass. Electrochimica Acta, 233, 274–283. DOI: 10.1016/j. electacta.2017.03.045.10.1016/j.electacta.2017.03.045
  6. 6. Dong, S., Wang, Z. & Wang, Y. (2017). High-speed electrochemical discharge drilling (HSECDD) for micro-holes on C17200 beryllium copper alloy in deionized water. The International J. Adv. Manufact. Technol. 88(1), 827–835. DOI: 10.1007/s00170-016-8645-x.10.1007/s00170-016-8645-x
  7. 7. Soundarrajan, M. & Thanigaivelan, R. (2019). Investigation of electrochemical micromachining process using ultrasonic heated electrolyte. Adv. Micro and Nano Manufact. Surf. Engin., Springer, Singapore, 423–434. DOI: 10.1007/978-981-32-9425-7_38.10.1007/978-981-32-9425-7_38
  8. 8. Rathod, V., Doloi, B. & Bhattacharyya, B. (2017). Fabrication of microgrooves with varied cross-sections by electro-chemical micromachining. Internat. J. Adv. Manufact. Technol., 92(1), 505–518. DOI: 10.1007/s00170-017-0167-7.10.1007/s00170-017-0167-7
  9. 9. Anasane, S.S. & Bhattacharyya, B. (2016). Experimental investigation on suitability of electrolytes for electrochemical micromachining of titanium. Internat. J. Adv. Manufact. Technol., 86(5), 2147–2160. DOI: 10.1007/s00170-015-8309-2.10.1007/s00170-015-8309-2
  10. 10. Thanigaivelan, R., Arunachalam, R.M., Kumar, M. & Dheeraj, B.P. (2018). Performance of electrochemical micromachining of copper through infrared heated electrolyte. Mater. Manufact. Proces., 33(4), 383–389. DOI: 10.1080/10426914.2017.1279304.10.1080/10426914.2017.1279304
  11. 11. Liu, W., Zhang, H., Luo, Z., Zhao, C., Ao, S., Gao, F. & Sun, Y. (2018). Electrochemical micromachining on titanium using the NaCl-containing ethylene glycol electrolyte. J. Mater. Proces. Technol., 255, 784–794. DOI: 10.1016/j. jmatprotec.2018.01.009.10.1016/j.jmatprotec.2018.01.009
  12. 12. Geethapriyan, T., Samson, R.M., Thavamani, J., Arun Raj, A.C. & Pulagam, B.R. (2019). Experimental investigation of electrochemical micro-machining process parameters on stainless steel 316 using sodium chloride electrolyte. Adv. Manufact. Proces. Springer, Singapore, 471-480. DOI: 10.1007/978-981-13-1724-8_45.10.1007/978-981-13-1724-8_45
  13. 13. Bhuyan, B.K. & Yadava, V. (2013). Experimental modeling and multi-objective optimization of traveling wire electro-chemical spark machining (TW-ECSM) process. J. Mech. Sci. Technol., 27(8), 2467–2476. DOI: 10.1007/s12206-013-0632-7.10.1007/s12206-013-0632-7
  14. 14. Sethi, A., Acharya, B.R. & Saha, P. (2022). Electrochemical dissolution of WC-Co micro-tool in micro-WECM using an Eco-friendly citric acid mixed NaNO3 electrolyte. J. The Electrochem. Soc., 169(3), 033503. DOI: 10.1149/1945-7111/ac54d9.10.1149/1945-7111/ac54d9
  15. 15. Yu, N., Fang, X., Meng, L., Zeng, Y. & Zhu, D. (2018). Electrochemical micromachining of titanium microstructures in an NaCl–ethylene glycol electrolyte. J. Appl. Electrochem., 48(3), 263–273. DOI: 10.1007/s10800-018-1145-y.10.1007/s10800-018-1145-y
  16. 16. Tak, M., Reddy S.V., Mishra, A. & Mote, R.G. (2018). Investigation of pulsed electrochemical micro-drilling on titanium alloy in the presence of complexing agent in electrolyte. J. Micromanufac., 1(2), 142–153. DOI: 10.1177/2516598418784682.10.1177/2516598418784682
  17. 17. Ma, N., Phattharasupakun, N., Wutthiprom, J., Tanggarnjanavalukul, C., Wuanprakhon, P., Kidkhunthod, P. & Sawangphruk, M. (2018). High-performance hybrid supercapacitor of mixed-valence manganese oxide/n-doped graphene aerogel nanoflower using an ionic liquid with a redox additive as the electrolyte: In situ electrochemical x-ray absorption spectroscopy. Electrochimica Acta, 271, 110–119. DOI: org/10.1016/j. electacta.2018.03.116.10.1016/j.electacta.2018.03.116
  18. 18. Singh, P.K., Das, A.K., Hatui, G. & Nayak, G.C. (2017). Shape controlled green synthesis of CuO nanoparticles through ultrasonic assisted electrochemical discharge process and its application for supercapacitor. Mater. Chem. Phys., 198, 16–34. DOI: 10.1016/j.matchemphys.2017.04.070.10.1016/j.matchemphys.2017.04.070
  19. 19. Sekar, T., Arularasu, M. & Sathiyamoorthy, V. (2016). Investigations on the effects of Nano-fluid in ECM of die steel. Measurement, 83, 38–43. DOI: 10.1016/j.measurement.2016.01.035.10.1016/j.measurement.2016.01.035
  20. 20. Jiang, K., Wu, X., Lei, J., Wu, Z., Wu, W., Li, W. & Diao, D. (2018). Vibration-assisted wire electrochemical micromachining with a suspension of B4C particles in the electrolyte. Internat. J. Adv. Manufac. Technol., 97(9), 3565–3574. DOI: 10.1007/s00170-018-2190-8.10.1007/s00170-018-2190-8
  21. 21. Geethapriyan, T., Muthuramalingam, T., Vasanth, S., Thavamani, J. & Srinivasan, V.H. (2019). Influence of nanoparticles-suspended electrolyte on machinability of stainless steel 430 using electrochemical micro-machining process. Adv. Manufac. Proces. Sprin., Singap. 433–440. DOI: 10.1007/978-981-13-1724-8_42.10.1007/978-981-13-1724-8_42
  22. 22. Kumaar, J.R.V., Thanigaivelan, R. & Soundarrajan, M. (2022). A performance study of electrochemical micro-machining on SS 316L using suspended copper metal powder along with stirring effect. Mater. Manufac. Proces., 1–14. DOI: 10.1080/10426914.2022.2030874.10.1080/10426914.2022.2030874
  23. 23. Yang, Y., Natsu, W. & Zhao, W. (2011). Realization of eco-friendly electrochemical micromachining using mineral water as an electrolyte. Precision Engin., 35(2), 204–213. DOI: 10.1016/j.precisioneng.2010.09.009.10.1016/j.precisioneng.2010.09.009
  24. 24. Geethapriyan, T., Kalaichelvan, K. & Muthuramalingam, T. (2016). Multi performance optimization of electrochemical micro-machining process surface related parameters on machining Inconel 718 using Taguchi-grey relational analysis. La Metallurgia Italiana, 2016(4), 13–19.
  25. 25. Fard, A.F. & Hajiaghaei-Keshteli, M. (2016). Red Deer Algorithm (RDA); a new optimization algorithm inspired by Red Deers’ mating. Internat. Confer. Ind. Engin., IEEE 12, 331–342.
  26. 26. Pradeep, N., Sundaram, K.S. & Kumar, M.P. (2020). Performance investigation of variant polymer graphite electrodes used in electrochemical micromachining of ASTM A240 grade 304. Mater. Manufact. Proces., 35(1), 72–85. DOI: 10.1080/10426914.2019.1697445.10.1080/10426914.2019.1697445
  27. 27. Krishnan, N., Deepak, J. & Hariharan, P. (2020). Multi-response optimization of electrochemical micromachining on masked SS304. Engin. Res. Express, 2(1), 015041. DOI: 10.1088/2631-8695/ab5eb9.10.1088/2631-8695/ab5eb9
  28. 28. Panigrahi, D., Rout, S., Patel, S.K. and Dhupal, D. (2021). Stray current and its consequences on microstructure of Hastelloy C-276 during parametric investigation on geometrical features: fabricated by electrochemical micromachining. Inter-nat. J. Adv. Manufact. Technol., 112(1), 133–156. DOI:10.1007/s00170-020-06365-9.10.1007/s00170-020-06365-9
  29. 29. Prakash, J. & Gopalakannan, S. (2021). Teaching— learning-based optimization coupled with response surface methodology for micro electrochemical machining of aluminium nanocomposite. Silicon, 13(2), 409–432. DOI: 10.1007/s12633-020-00434-0.10.1007/s12633-020-00434-0
  30. 30. Ranganayakulu, J., Srihari, P.V. & Rao, K.V. (2021). An optimization strategy to improve performance in electrochemical discharge machining of borosilicate glass using graph theory algorithm and desirability index. Silicon, 1–14. DOI: 10.1007/s12633-021-01317-8.10.1007/s12633-021-01317-8
  31. 31. Gautam, N., Goyal, A., Sharma, S.S., Oza, A.D. & Kumar, R., 2022. Study of various optimization techniques for electric discharge machining and electrochemical machining processes. Materials Today: Proceedings, 57, 615–621. DOI: 10.1016/j.matpr.2022.02.005.10.1016/j.matpr.2022.02.005
  32. 32. Aslan, N.E.V.Z.A.T. & Cebeci, Y.A.K.U.P. (2007). Application of Box–Behnken design and response surface methodology for modeling of some Turkish coals. Fuel, 86(1–2), 90–97. DOI: 10.1016/j.fuel.2006.06.010.10.1016/j.fuel.2006.06.010
  33. 33. Barabadi, H., Honary, S., Ebrahimi, P., Alizadeh, A., Naghibi, F. & Saravanan, M. (2019). Optimization of myco-synthesized silver nanoparticles by response surface methodology employing Box-Behnken design. Inorganic and Nano-Metal Chemistry, 49(2), 33–43. DOI: 10.1080/24701556.2019.1583251.10.1080/24701556.2019.1583251
  34. 34. Kim, S.G., Harwani, M., Grama, A. & Chaterji, S. (2016). EP-DNN: a deep neural network-based global enhancer prediction algorithm. Scientific reports, 6(1), 1–13. DOI: 10.1038/srep38433.10.1038/srep38433514406227929098
  35. 35. Brammya, G., Praveena, S., Ninu Preetha, N.S., Ramya, R., Rajakumar, B.R. & Binu, D. (2019). Deer hunting optimization algorithm: a new nature-inspired meta-heuristic paradigm. Comp. J. DOI: 10.1093/comjnl/bxy133.10.1093/comjnl/bxy133
  36. 36. Elhami, S. & Razfar, M.R. (2020). Application of nano electrolyte in the electrochemical discharge machining process. Precision Engin., 64, 34–44. DOI: 10.1016/j.precisioneng.2020.03.010.10.1016/j.precisioneng.2020.03.010
  37. 37. Teimouri, R. & Sohrabpoor, H. (2013). Application of adaptive neuro-fuzzy inference system and cuckoo optimization algorithm for analyzing electro chemical machining process. Front. Mech. Engin., 8(4), 429–442. DOI: 10.1007/s11465-013-0277-3.10.1007/s11465-013-0277-3
  38. 38. Charak, A. & Jawalkar, C.S. (2020). Experimental studies in micro channelling on borosilicate glass using RSM optimization technique. Silicon, 12(7), 1707–1721. DOI: 10.1007/s12633-019-00269-4.10.1007/s12633-019-00269-4
  39. 39. Rajput, V., Goud, M. & Suri, N.M. (2021). Performance analysis of closed-loop electrochemical discharge machining (CLECDM) during micro-drilling and response surface methodology based multi-response parametric optimization. Adv. Mater. Process. Technol.1–31. DOI: 10.1080/2374068X.2020.1860494.10.1080/2374068X.2020.1860494
  40. 40. Gopinath, C., Lakshmanan, P. & Amith, S.C. (2021). Production of Micro-holes on Duplex Stainless Steel 2205 by Electrochemical Micromachining: A Grey-RSM Approach. Arabian J. Sci. Engin., 46(3), 2769–2782. DOI: 10.1007/s13369-020-05277-w.10.1007/s13369-020-05277-w
Language: English
Page range: 7 - 22
Published on: Dec 26, 2022
Published by: West Pomeranian University of Technology, Szczecin
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2022 Vijayakumar Kanniyappan, Sekar Tamilperuvalathan, published by West Pomeranian University of Technology, Szczecin
This work is licensed under the Creative Commons Attribution 4.0 License.