Modeling and multi-objective optimization of low-frequency vibration-assisted chemical machining using central composite design in response surface methodology

Document Type : Article

Authors

1 Mechanical Engineering Faculty, Department of Engineering, University of Zanjan, Zanjan, Iran

2 - Mechanical Engineering Faculty, Department of Engineering, University of Zanjan, Zanjan, Iran - Department of Mechanical Engineering, School of Engineering and Applied Science, Khazar University, Baku, Azerbaijan

Abstract

Increasing the etching rate is one of the main optimization targets in the chemical machining (CM). Traditionally, this target is fulfilled by some costly techniques like selecting stronger etchants and increasing the etchant concentration. Also, other methods like increasing the etchant temperature and stirring the etchants by agitators are employed for increasing the etching rate. One of the advantages of these methods is reduction of the consumption of acidic etchants which results in the cost reduction and making an eco-friendley process. In this article, a systematic experimental study is performed on vibration-assisted CM of copper. In this technique, the workpiece vibrates in the etchant during the CM. For evaluating the performance of machining, effects of amplitude and frequency of vibrations, along with the temperature and concentration of acidic etchant, on material removal rate, surface roughness and machining undercut are studied experimentally. The experiments are designed by Central Composite Design (CCD) in Response Surface Methodology (RSM). Also, multi-objective optimization is performed by defining a desirability function. The optimal vibro-assisted process parameters are temperature 60 ̊C, etchant concentration 600 g/l, vibration frequency 25 Hz, and vibration amplitude 1.5 mm, to get optimal outputs on the desired parameters.

Keywords

Main Subjects


References:
1. Jain, V.K. "Advanced machining processes", Allied Publishers (2009). https://doi.org/10.1007/978-1-84800-213-5 11.
2. Rohith, R., Ruthvik, G., Raju, K., et al. "Chemical machining process-a review", Proceedings on Engineering, 4(1), pp. 33-36 (2022). https://doi.org/10.24874/pes04.01.005.
3. Raut, M.A., Kale, S.S., and Pangavkar, P.V. "Fabrication of micro channel heat sink by using photo chemical machining", Int J New Technol Res, 5(4), pp. 72-75 (2019). https://doi.org/10.31871/ijntr.5.4.30.
4. Wagh, D., Dolas, D., and Dhagate, M. "Experimental investigation of photochemical machining on Inconel 600 using ferric chloride", International Journal of Engineering Research & Technology, 4(2), pp. 289-293 (2014).
5. Wangikar, S.S., Patowari, P.K., and Misra, R.D. "Parametric optimization for photochemical machining of copper using overall evaluation criteria", Materials Today: Proceedings, 5(2), pp. 4736-4742 (2018). https://doi.org/10.1016/j.matpr.2017.12.046.
6. Kamble, B., Utpat, A., and Misal, N., et al., Effect of Process Parameters on Response Measures of Cartridge Brass Material in Photo Chemical Machining, in Techno-Societal 2020: Springer, pp. 995-1003 (2021). https://doi.org/10.1007/978-3-030-69921-5 99.
7. Gangmei, G., Kumar, J., Debnath, T., et al., Parametric Analysis for Machining of Stainless Steel AISI (SS-430) Using Photo Chemical Machining, in Recent Advances in Mechanical Engineering: Springer, pp. 829-837 (2021). https://doi.org/10.1007/978-981-15-7711-6 82.
8. Mazarbhuiya, R.M. and Rahang, M., Parametric Study of Photochemical Machining of Aluminium Using Taguchi Approach, in Advances in Mechanical Engineering, Springer, pp. 497-504 (2020). https://doi.org/10.1007/978-981-15-0124-1 45.
9. Ibrahim, A., Abdulwahhab, A., and Shabeeb, A. "Influence of fecl3 on material removal rate and surface roughness in chemical machining process", Kufa Journal of Engineering, 10(1), pp. 44-55 (2019). https://doi.org/10.30572/2018/kje/100104.
10. Gandhi, S.V. and Rahul, M.C. "Experimental investigation of wet chemical machining and optimization of process parameters using grey relational analysis for SS 316L", Materials Today: Proceedings, 5(1), pp. 23908- 23916 (2018). https://doi.org/10.1016/j.matpr.2018.10.183.
11. Mazarbhuiya, R.M. and Rahang, M. "Parametric optimization in photochemical machining of aluminium using Taguchi method", in IOP Conference Series: Materials Science and Engineering, 491(1), IOP Publishing, p. 012033 (2019).https://doi.org/10.1088/1757-899x/491/1/012033.
12. Patil, D.H., Thorat, S.B., Khake, R.A., et al. "Comparative study of FeCl3 and CuCl2 on geometrical features using photochemical machining of monel 400", Procedia CIRP, 68, pp. 144-149 (2018). https://doi.org/10.1016/j.procir.2017.12.084.
13. C akr, O. "Chemical machining of St37 rod using etchant dubstance FeCl3", Acta Physica Polonica A, 135(4), pp. 583-585 (2019). https://doi.org/10.12693/aphyspola.135.583.
14. Ruhela, V., Ansari, M.I., Jadhav, P.V., et al. "An experimental investigation of photo chemical machining process for stainless-steel material by using different etchants", Materials Today: Proceedings (2023). https://doi.org/10.1016/j.matpr.2023.03.324.
15. Gandhi, S.V. and Chanmanwar, R. "A study of variation in MRR influenced by work piece positioning on copper and stainless tseel during wet chemical machining", in International Conference on Advances in Thermal Systems, Materials and Design Engineering (ATSMDE2017) (2017). https://doi.org/10.2139/ssrn.3101587.
16. Saraf, A.R. and Sadaiah, M. "Photochemical machining of a novel cardiovascular stent", Materials and Manufacturing Processes, 32(15), pp. 1740-1746 (2017). https://doi.org/10.1080/10426914.2016.1198025.
17. Yang, M.Y. and Youn, J.W. "Ultrasonic-assisted chemical machining of fine rods", Wear, 145(2), pp. 303-313 (1991).https://doi.org/10.1016/0043-1648(91)90138-k.
18. Bahrami, P., Khoshanjam, A., and Azizi, A. "Evaluation of fatigue behavior and surface characteristics of novel machining process: Rotary chemical machining (RCM)", ADMT Journal, 14(3), pp. 17-24 (2021).
19. Wang, J., Sun, Q., and Sun, P. "Research status and prospect of laser scribing process and equipment for chemical milling parts in aviation and aerospace", Micromachines, 13(2), p. 323 (2022).https://doi.org/10.3390/mi13020323.
20. Khuri, A.I. and Mukhopadhyay, S. "Response surface methodology", Wiley Interdisciplinary Reviews: Computational Statistics, 2(2), pp. 128-149 (2010). https://doi.org/10.1002/wics.73.
21. Mumbare, P. and Gujar, A. "Multi objective optimization of photochemical machining for ASME 316 steel using grey relational analysis", International Journal of Innovative Research in Science, Engineering and Technology, 5(7), pp. 12418-12425 (2016). DOI: 10.15680/IJIRSET.2016.0507050.
22. Chanmanwar, R., Balasubramaniam, R., Sapkal, S.U., et al. "Fabrication of microchannels on SS-304 and copper by wet chemical etching and comparison of topographies", in International Conference on Advances in Thermal Systems, Materials and Design Engineering (2017).https://doi.org/10.1016/0043-1648(91)90138-k.
23. Whitcomb, P.J. and Anderson, M.J. "Optimizing processes using response surface methods for design of experiments", RSM Simplified, CRC Press (2004). https://doi.org/10.4324/9781482293777.
24. Akcay, H. and Anagun, A.S. "Multi response optimization application on a manufacturing factory", Mathematical and Computational Applications, 18(3), pp. 531-538 (2013). https://doi.org/10.3390/mca18030531.
25. Jian, C., Jusheng, M., Gangqiang, W., et al. "Effects on etching rates of copper in ferric chloride solutions", in 2nd 1998 IEMT/IMC Symposium (IEEE Cat. No. 98EX225), IEEE, pp. 144-148 (1998). https://doi.org/10.1109/iemtim.1998.704541.
26. Yadav, S., Saraf, A., and Sadaiah, M. "Analysis of undercut for SS304 in photochemical machining", inInternational Conference on Communication and Signal Processing 2016 (ICCASP 2016), Atlantis Press, pp. 284-289 (2016). https://doi.org/10.2991/iccasp-16.2017.45.
27. Saraf, A.R., Sadaiah, M., and Devkare, S. "Optimization of photochemical machining", International Journal of Engineering Science and Technology, 1(3), pp. 7108-7116 (2011). https://doi.org/10.4028/www.scientific.net/amr.548.617.
28. Nemati, B., Mohamamdi, M.M., and Moharrami, R. "Multi-objective optimization of electrochemical finishing for attaining the required surface finish and geometric accuracy in the hole making process", Scientia Iranica, 31(4), pp. 283-294 (2023). https://doi.org/10.24200/sci.2023.58585.5802.