Investigation and Optimization of the Effect of Input Parameters on Material Removal Rate, Tool Wear Rate, and Surface Roughness in Electrical Discharge Machining of A356 Nano-Composite Reinforced By Alumina

Subject Areas :

Mohammad Javad HajHosseini ¹ , Ali Mokhtarian ² , Mojtaba Rahimi ³ , Behnam Masoudi ⁴

1 - Department of Mechanical, Civil, and Architectural Engineering, Khomeinishahr Branch, Islamic Azad University, Khomeinishahr/Isfahan, Iran
2 - Department of Mechanical, Civil, and Architectural Engineering, Khomeinishahr Branch, Islamic Azad University, Khomeinishahr/Isfahan, Iran.
3 - Department of Mechanical, Civil, and Architectural Engineering, Khomeinishahr Branch, Islamic Azad University, Khomeinishahr/Isfahan, Iran.
4 - Department of Mechanical, Civil, and Architectural Engineering, Khomeinishahr Branch, Islamic Azad University, Khomeinishahr/Isfahan, Iran.

Received: 2021-06-23 Accepted : 2021-12-20 Published : 2022-10-23

Keywords: Electrical Discharge Machining Nano, Composite Taguchi Technique Signal to Noise Ratio Variance Analysis,

Abstract :

In this research, the effect of input parameters of Electrical Discharge Machining (EDM) on A356 nano-composite reinforced by 3.5% alumina (Al2O3) was examined and optimized by the Taguchi technique based on the L9 orthogonal array and duplicated levels technique. The input parameters of these experiments consisted of voltage (two-level), current intensity (three-level), pulse on-time (three-level), and pulse off-time (three-level). Moreover, the output parameters were comprised of the material removal rate of the workpiece, the tool wear rate of the machining, and the surface roughness of the workpiece. The analysis of the results and investigation of the signal-to-noise graphs (S/N) and variance analysis (ANOVA) were carried out by using software. Also, with the determination of the loss function of total normalized values of the output parameters based on appropriate weight coefficients, the optimum level of each input parameter was identified. Besides, with performing the variance analysis, the magnitude of contribution percentage of each of the input parameters in the total variance was calculated. Based on the obtained results, it was concluded that the most influential parameter on the material removal rate was the pulse off-time, on tool wear rate was the current intensity, and on the surface roughness was the pulse on-time. Furthermore, the first level of the voltage (80 V), the first level of the current intensity (10 A), the first level of the pulse on-time (35 µs), and the second level of the pulse off-time (70 µs) were determined as the optimum input parameters. The contribution percentage of the input parameters in the total variance for voltage, current intensity, pulse on-time, and pulse off-time was found to be 12.98, 20.96, 5.47, and 60.60, respectively.

References:

 [1] ف. بیغال، "روش­های ماشین­کاری مدرن"، انتشارات طراح، چاپ ششم، 1389.

[2] D. Naderi & E. Ghasemi, "Fundamentals of machining using spark and wire cut", Tarrah publication, 2009.

 

[3] A. Erden & S. Bilgin, "Role of impurities in electric discharge machining, in: 21st Conference of Machine Tool Design and Research", London, pp. 345-350, 1980.

 

[4] H. K. Kansal, S. Singh & P. Kumara, "EDM drilling optimization using stochastic techniques", Procedia CIRP, vol. 67, pp. 350-355, 2018.

 

[5] Q. Y. Ming & L. Y. He, "Thermographic analysis of spark location distribution in sinking EDM", Procedia CIRP, vol. 68, pp. 280-285, 2018.

 

[6] ه. فتاحی و ع. پاک، "بررسی فرآیند ماشین­کاری تخلیه‌ الکتریکی به کمک امواج فراصوتی با استفاده از مخلوط نانو‌پودرهای اکسید تیتانیوم، اکسید روی و اکسید آلومینیوم در دی‌الکتریک"، نشریه مهندسی مکانیک امیرکبیر، دوره 50، شماره 3، صفحه 550-541، 1397.

 

[7] S. S. Sidhu, A. Batish & S. Kumar, "Improving EDM performance by adapting gap servo-voltage to machining state", Journal of Manufacturing Processes, vol. 37, pp. 101-113, 2019.

 

[8] B. Mohan, A. Rajadurai & K. G. Satyanarayana, "Study on micro reciprocated wire-EDM for complex indexing structure", Procedia CIRP, vol. 68, pp. 120-125, 2018.

 

[9] P. Kuppan, A. Rajadurai & S. Narayanan, "Pulse efficiency and gap status of rotary ultrasonic assisted electrical discharge machining and EDM milling", Procedia CIRP, vol. 68, pp. 783-788, 2018.

 

[10] A. Dev, K. M. Patel, P. M. Pandey & S. Aravindan, "Multi-characteristics optimization in EDM of NiTi alloy, NiCu alloy and BeCu alloy using Taguchi’s approach and utility concept", Alexandria engineering journal, vol. 57, no. 4, pp. 2807-2817, 2018.

 

[11] P. M. George, B. K. Ragunath, L. M. Manocha & A. M. Warrier, "EDM machining of carbon-carbon composite-a Taguchi approach", Journal of Materials Processing Technology, vol. 145, no. 1, pp. 66-71, 2004.

 

[12] T. Rajmohan & R. Prubho, "Optimization of machining parameter in EDM of 304 stainless steel", Procedia Engineering, vol. 38, pp. 1030-1036, 2012.

[13] S. Gopakalannan, T. Sinthelevan & S. Ranganathan, "Modeling and optimization of EDM process parameter on machining of AL 7075-B4 MMC using RSM", Procedia Engineering, vol. 38, pp. 685-690, 2012.

 

[14] M. S. Dastjerdi, A. Mokhtarian & P. Saraeian, "The effect of alumina powder in dielectric on electrical discharge machining parameters of aluminum composite A413-Al2O3 by the Taguchi method, the signal-to-noise analysis and the total normalized quality loss", International Journal of Mechanical and Materials engineering, vol. 15, no. 5, pp. 1-11, 2020.

 

[15] ع. ا. لطفی نیستانک و س. دانشمند، "ﺑﺮرﺳﯽ ماشین‌کاری تخلیه الکتریکی ماده مرکب آلومینیوم تقویت شده با نانو ذرات اکسید تیتانیوم"، فصلنامه علمی پژوهشی فرآیندهای نوین در مهندسی مواد، سال سیزدهم، شماره دوم، صفحه 43-27، 1398.

 

[16] S. A. Sajjadi, M. Torabi Parizi, H. R. Ezatpour & A. Sedghi, "Fabrication of A356 composite reinforced with micro and nano Al2O3 particles by a developed compocasting method and study of its properties", Journal of Alloys and Compounds, vol. 511, no. 1, pp. 226–231, 2012.

 

[17] ب. مسعودی و س. دانشمند، "ﺑﺮرﺳﯽ تأثیر ﭘﺎراﻣﺘﺮﻫﺎی ماشین‌کاری تخلیه الکتریکی، بر روی ماده مرکب پایه آلومینیوم 2024 با استفاده از تحلیل مقدار کل نرمال شده پارامترها (TNQL) و نسبت سیگنال به نویز(S/N)"، فصلنامه علمی پژوهشی فرآیندهای نوین در مهندسی مواد، سال یازدهم، شماره اول، صفحه 110-91، 1396.

 

[18] J. Antony, "Simultaneous Optimisation of multiple quality characteristics in manufacturing processes using Taguchi’s quality loss function", The International Journal of Advanced Manufacturing Technology, vol. 17, pp.  134-138, 2001.

 

[19] G. Taguchi, "Taguchi quality engineering handbook", Wiley, 2005.

 

[20] M. Karimi, M. R. Toroghinejad & K. Farmanesh, "Multi-response optimization on the annealing of accumulative roll bonded monolithic Ti and Ti–SiC_p composites", Materials & Design, vol. 65, pp. 34-41, 2015.

 

[21] M. Yousefieh, M. Shamanian & A. Saatchi, "Optimization of the pulsed current gas tungsten arc welding (PCGTAW) parameters for corrosion resistance of super duplex stainless steel (UNS S32760) welds using the Taguchi method", Journal of Alloys and Compounds, vol. 509, pp. 782-788, 2011.

 

[22] Y. Ma, H. Hu, D. Northwood & X. Nie, "Optimization of the electrolytic plasma oxidation processes for corrosion protection of magnesium alloy AM50 using the Taguchi method", Journal of Materials Processing Technology, vol. 182, pp. 58-64, 2007.