Abstract
This research addresses electrical discharge machining of engineered Al-22%SiC metal matrix composite to analyze the surface roughness of machined part. A series of machining trials are performed under varied process conditions (flushing pressure, gap voltage, pulse-on time, discharge current, pulse-off time) obtained by Box–Behnken design. Additionally, this work addresses on desirability optimization methodology and predictive modeling for minimization of machined surface quality employing response surface methodology. Based on the motivational viewpoint of “Go green-Think green-Act green,” a unique approach has been suggested for economic analysis and sustainability assessment to determine the overall machining cost per part and to justify the usefulness of vegetable oil as dielectric medium in electrical discharge machining. According to statistical analysis, the contribution of spark discharge current was identified as the leading factor in surface quality degradation. The estimated optimal surface roughness of 0.181 µm and the calculated overall machining cost per part of Rs.245.9 were preferred at a pulse-on time of 100 µs, gap voltage of 1 V, pulse-off time of 30 µs, discharge current of 4 A, and flushing pressure of 0.57 kgf/cm2, which indicates techno-economically viable. The vegetable oil considered as dielectric fluid is biodegradable and environmentally safe, thus contributing to sustainable production.
Similar content being viewed by others
Data Availability
Not applicable.
References
Belloufi A, Mezoudj M, Abdelkrim M, Rezgui I, Chiba E (2020) Experimental and predictive study by multi-output fuzzy model of electrical discharge machining performances. The International Journal of Advanced Manufacturing Technology. https://doi.org/10.1007/s00170-020-05718-8
Bharti PS, Maheshwari S, Sharma C (2012) Multi-objective optimization of electric-discharge machining process using controlled elitist NSGA-II. J Mech Sci Technol 26(6):1875–1883
Cakir MV, Eyercioglu O, Gov K, Sahin M, Cakir SH (2013) Comparison of soft computing techniques for modelling of the EDM performance parameters. Adv Mech Eng. https://doi.org/10.1155/2013/392531
Chattopadhyay KD, Verma S, Satsangi PS, Sharma PC (2009) Development of empirical model for different process parameters during rotary electrical discharge machining of copper–steel (EN-8) system. J Mater Process Technol 209(3):1454–1465
Chaudhury P, Samantaray S (2021) Modelling and optimization of machining of SiC-CNT conductive ceramic composite used for micro and nano sensor by electrical discharge machining. J Inst Eng India Ser D. https://doi.org/10.1007/s40033-021-00256-3
Chen Z, Zhou H, Yan Z, Han F, Yan H (2021) Machining characteristics of 65 vol.% SiCp/Al composite in micro-WEDM. Ceramics International 47(10):13533–13543
Chen Z, Yan Z, Zhou H, Han F, Zhao L, Yan H (2021) One-step fabrication of the wear-resistant superhydrophobic structure on SiCp/Al composite surface by WEDM. Surface and Coatings Technology 409:126876
D’Urso G, Giardini C, Ravasio C (2018) Effects of electrode and workpiece materials on the sustainability of micro-EDM drilling process. Int J Precis Eng Manuf 19(11):1727–1734
Dash L, Padhan S, Das SR (2020) Experimental investigations on surface integrity and chip morphology in hard tuning of AISI D3 steel under sustainable nanofluid-based minimum quantity lubrication. Journal of the Brazilian Society of Mechanical Sciences and Engineering 42:10
Gao Q, Zhang Q, Su S, Zhang J (2008) Parameter optimization model in electrical discharge machining process. Journal of Zhejiang University-SCIENCE A 9(1):104–108
Gohil V, Puri YM (2016) Statistical analysis of material removal rate and surface roughness in electrical discharge turning of titanium alloy (Ti-6Al-4V). Proceedings of the Institution of Mechanical Engineers, Part b: Journal of Engineering Manufacture 232(9):1603–1614
Gopalakannan S, Senthilvelan T (2013) A parametric study of electrical discharge machining process parameters on machining of cast Al/B4C metal matrix nanocomposites. Proceedings of the Institution of Mechanical Engineers, Part b: Journal of Engineering Manufacture 227(7):993–1004
Hanif M, Wasim A, Shah AH, Noor S, Sajid M, Mujtaba N (2019) Optimization of process parameters using graphene-based dielectric in electric discharge machining of AISI D2 steel. The International Journal of Advanced Manufacturing Technology 103:3735–3749
Jagadish Kumar S, Soni DL (2021) Performance analysis and optimization of different electrode materials and dielectric fluids on machining of high carbon high chromium steel in electrical discharge machining. Proc Natl Acad Sci, India, Sect A Phys Sci. https://doi.org/10.1007/s40010-020-00727-4
Keskin Y, Halkacı HS, Kizil M (2005) An experimental study for determination of the effects of machining parameters on surface roughness in electrical discharge machining (EDM). The International Journal of Advanced Manufacturing Technology 28(11–12):1118–1121
Kumar S, Batish A, Singh R, Singh TP (2014) A hybrid Taguchi-artificial neural network approach to predict surface roughness during electric discharge machining of titanium alloys. J Mech Sci Technol 28(7):2831–2844
Kumar S, Dhingra AK, Kumar S (2017) Parametric optimization of powder mixed electrical discharge machining for nickel-based superalloy inconel-800 using response surface methodology. Mechanics of Advanced Materials and Modern Processes 3:7
Majumder A (2014) Comparative study of three evolutionary algorithms coupled with neural network model for optimization of electric discharge machining process parameters. Proceedings of the Institution of Mechanical Engineers, Part b: Journal of Engineering Manufacture 229(9):1504–1516
Marichamy S, Saravanan M, Ravichandran M, Veerappan G (2016) Parametric optimization of electrical discharge machining process on α–β brass using grey relational analysis. J Mater Res 31(16):2531–2537
Markopoulos AP, Manolakos DE, Vaxevanidis NM (2008) Artificial neural network models for the prediction of surface roughness in electrical discharge machining. J Intell Manuf 19(3):283–292
Mohan B, Rajadurai A, Satyanarayana KG (2004) Electric discharge machining of Al–SiC metal matrix composites using rotary tube electrode. J Mater Process Technol 153–154:978–985
Mohanty CP, Mahapatra SS, Singh MR (2014) A particle swarm approach for multi-objective optimization of electrical discharge machining process. J Intell Manuf 27(6):1171–1190
Mohanty CP, Mahapatra SS, Singh MR (2017) An intelligent approach to optimize the EDM process parameters using utility concept and QPSO algorithm. Engineering Science and Technology, an International Journal 20(2):552–562
Muthuramalingam T, Mohan B (2013) Influence of discharge current pulse on machinability in electrical discharge machining. Mater Manuf Processes 28(4):375–380
Naik S, Das SR, Dhupal D (2020) Analysis, predictive modelling and multi-response optimization in electrical discharge machining of Al-22%SiC metal matrix composite for minimization of surface roughness and hole overcut. Manuf Rev 7:20
Naik S, Das SR, Dhupal D (2021) Experimental investigation, predictive modeling, parametric optimization and cost analysis in electrical discharge machining of Al-SiC metal matrix composite. SILICON 13:1017–1040
Pellegrini G, Ravasio C (2019) Evaluation of the sustainability of the micro-electrical discharge milling process. Advances in Production Engineering & Management 14(3):343–354
Prabhu S, Uma M, Vinayagam BK (2013) Electrical discharge machining parameters optimization using response surface methodology and fuzzy logic modeling. J Braz Soc Mech Sci Eng 36(3):637–652
Pradhan MK, Das R, Biswas CK (2009) Comparisons of neural network models on surface roughness in electrical discharge machining. Proceedings of the Institution of Mechanical Engineers, Part b: Journal of Engineering Manufacture 223(7):801–808
Prakash C, Kansal HK, Pabla BS, Puri S (2016) Multi-objective optimization of powder mixed electric discharge machining parameters for fabrication of biocompatible layer on β-Ti alloy using NSGA-II coupled with Taguchi based response surface methodology. J Mech Sci Technol 30(9):4195–4204
Puertas I, Perez CJL (2003) Modelling the manufacturing parameters in electrical discharge machining of siliconized silicon carbide. Proceedings of the Institution of Mechanical Engineers, Part b: Journal of Engineering Manufacture 217(6):791–803
Rahul Datta S, Biswal BB, Mahapatra SS (2017) A novel satisfaction function and distance-based approach for machining performance optimization during electro-discharge machining on super alloy Inconel 718. Arabian Journal for Science and Engineering 42(5):1999–2020
Rahul Datta S, Biswal BB, Mahapatra SS (2019) Machinability analysis of Inconel 601, 625, 718 and 825 during electro-discharge machining: on evaluation of optimal parameters setting. Measurement 137:382–400
Ramesh S, Jenarthanan M (2021) Optimizing the powder mixed EDM process of nickel based super alloy. Proceedings of the Institution of Mechanical Engineers, Part e: Journal of Process Mechanical Engineering. https://doi.org/10.1177/09544089211002782
Raza MH, Wasim A, Ali MA, Hussain S, Jahanzaib M (2018) Investigating the effects of different electrodes on Al6061-SiC-7.5 wt% during electric discharge machining. The International Journal of Advanced Manufacturing Technology 99(9–12):3017–3034
Reddy VV, Valli PM, Kumar A, Reddy CS (2014) Multi-objective optimization of electrical discharge machining of PH17-4 stainless steel with surfactant-mixed and graphite powder–mixed dielectric using Taguchi-data envelopment analysis–based ranking method. Proceedings of the Institution of Mechanical Engineers, Part b: Journal of Engineering Manufacture 229(3):487–494
Sahu SK, Datta S (2019) Experimental studies on graphite powder-mixed electro-discharge machining of Inconel 718 super alloys: comparison with conventional electro-discharge machining. Proceedings of the Institution of Mechanical Engineers, Part e: Journal of Process Mechanical Engineering 233(2):384–402
Sahu SK, Jadam T, Datta S, Nandi G (2018) Effect of using SiC powder-added dielectric media during electro-discharge machining of Inconel 718 superalloys. J Braz Soc Mech Sci Eng 40(7):300
Sahu AK, Thomas J, Mahapatra SS (2020) An intelligent approach to optimize the electrical discharge machining of titanium alloy by simple optimization algorithm. Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, 095440892096468. https://doi.org/10.1177/0954408920964685
Selvarajan L, Manohar M, Udhayakumar A, Dhinakaran P (2017) Modelling and experimental investigation of process parameters in EDM of Si3N4-TiN composites using GRA-RSM. Journal of Mechanical Science and Technology 31(1):111–122
Senthil Kumar R, Suresh P (2019) Experimental study on electrical discharge machining of Inconel using RSM and NSGA optimization technique. J Braz Soc Mech Sci Eng 41:35
Shabgard MR, Farahmand MR, Ivanov A (2009) Mathematical modelling and comparative study of the machining characteristics in ultrasonic-assisted electrical discharge machining of cemented tungsten carbide (WC–10%Co). Proceedings of the Institution of Mechanical Engineers, Part b: Journal of Engineering Manufacture 223(9):1115–1126
Singh S (2012) Optimization of machining characteristics in electric discharge machining of 6061Al/Al2O3p/20P composites by grey relational analysis. The International Journal of Advanced Manufacturing Technology 63(9–12):1191–1202
Singh J, Sharma RK (2017) Multi-objective optimization of green powder-mixed electrical discharge machining of tungsten carbide alloy. Proc Inst Mech Eng C J Mech Eng Sci 232(16):2774–2786
Singh B, Kumar J, Kumar S (2015) Optimization and surface modification in electrical discharge machining of AA 6061/SiCp composite using Cu–W electrode. Proceedings of the Institution of Mechanical Engineers, Part l: Journal of Materials: Design and Applications 231(3):332–348
Singh NK, Kumar S, Singh Y, Sharma V (2019) Predictive analysis of surface finish in gas assisted electrical discharge machining using statistical and soft computing techniques. Surf Rev Lett. https://doi.org/10.1142/s0218625x19501269
Sivam SP, Michaelraj AL, Kumar SS, Prabhakaran G, Dinakaran D, Ilankumaran V (2013) Statistical multi-objective optimization of electrical discharge machining parameters in machining titanium grade 5 alloy using graphite electrode. Proceedings of the Institution of Mechanical Engineers, Part b: Journal of Engineering Manufacture 228(7):736–743
Srinivas Viswanth V, Ramanujam R, Rajyalakshmi G (2018) A review of research scope on sustainable and eco-friendly electrical discharge machining (E-EDM). Materials Today: Proceedings 5(5):12525–12533
Talla G, Sahoo DK, Gangopadhyay S, Biswas CK (2015) Modeling and multi-objective optimization of powder mixed electric discharge machining process of aluminum/alumina metal matrix composite. Engineering Science and Technology, an International Journal 18(3):369–373
Tang L, Du YT (2013) Experimental study on green electrical discharge machining in tap water of Ti–6Al–4V and parameters optimization. The International Journal of Advanced Manufacturing Technology 70(1–4):469–475
Tang L, Guo YF (2013) Electrical discharge precision machining parameters optimization investigation on S-03 special stainless steel. The International Journal of Advanced Manufacturing Technology 70(5–8):1369–1376
Tzeng C-J, Chen R-Y (2013) Optimization of electric discharge machining process using the response surface methodology and genetic algorithm approach. Int J Precis Eng Manuf 14(5):709–717
Valaki JB, Rathod PP, Sankhavara CD (2016) Investigations on technical feasibility of Jatropha curcas oil based bio dielectric fluid for sustainable electric discharge machining (EDM). J Manuf Process 22:151–160
Yadav US, Yadava V (2014) Experimental modeling and multiobjective optimization of electrical discharge drilling of aerospace superalloy material. Proceedings of the Institution of Mechanical Engineers, Part b: Journal of Engineering Manufacture 229(10):1764–1780
Yan H, BakadiasaKabongo D, Yan Z, Han F, Chen Z (2020) Sustainable production of high-uniformity workpiece surface quality in wire electrical discharge machining by fabricating surface microstructure on wire electrode. Journal of Cleaner Production 259:120881
Yildiz Y, Sundaram MM, Rajurkar KP (2012) Statistical analysis and optimization study on the machinability of beryllium–copper alloy in electro discharge machining. Proceedings of the Institution of Mechanical Engineers, Part b: Journal of Engineering Manufacture 226(11):1847–1861
Author information
Authors and Affiliations
Contributions
The authors have made substantial contributions to the conception and design of the study, in the acquisition of the data, and in the analysis and interpretation of the data. The authors participated in drafting the article critically for important intellectual content.
Corresponding author
Ethics declarations
Ethics Approval and Consent to Participate
Not applicable.
Consent for Publication
Not applicable.
Competing Interests
The authors declare no competing interests.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Naik, S., Das, S.R., Dhupal, D. et al. Electrical Discharge Machining of Engineered Al-22%SiC Metal Matrix Composite: Surface Roughness Analysis, Optimization, Economic Analysis, and Sustainability Assessment. Process Integr Optim Sustain 6, 223–251 (2022). https://doi.org/10.1007/s41660-021-00207-1
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s41660-021-00207-1