Abstract
Fabrication of 316L steel with the desired surface integrity and thin modified recast layer for manufacturing various devices is very challenging using the traditional techniques and requires post-processing. Nevertheless, electro-discharge machining (EDM) is an evolving candidate among the non-traditional processes offering concurrent machining and surface alteration for the instrument manufacturing industry. To explore its full potential, this research work provides a thorough investigation of process variables on the machining performances and surface features primarily required for processing 316L steel in the industry. In this study, nano multi-walled carbon nanotubes (MWCNT) are utilized to improve the machining and surface responses. In addition to this, the parametric optimization is conducted through a Taguchi-based design which assists to obtain the highest material removal rate (MRR) of 42.25 mg/min corresponding to a 10-A peak current, 16-μs pulse-on time, 1-g/l MWCNT amount, and 45% duty cycle while the lowest surface roughness (SR) and recast layer thickness (RLT) of 1.58 μm and 5.243 μm respectively are attained at a 5-A peak current, 8-μs pulse-on time, 0.7-g/l MWCNT amount, and 45% duty cycle. Analysis of variance (ANOVA) reports peak current being the most momentous parameter complied by the MWCNT amount, pulse-on time, and duty cycle for MRR, SR, and RLT. The best 21 solution sets predicted through the multi-objective optimization tool called non-dominated sorting genetic algorithm-II (NSGA-II) obeying the set objective functions are proposed which are obtained from the Pareto optimal frontiers. Accuracy levels of the predicted solution sets are verified by the confirmatory experiments showing the estimated errors of less than 10%. SEM analyses confirm excellent surface integrity with a comparatively thin recast layer formation.
Similar content being viewed by others
Data availability
The authors have ensured 100% data transparency. All data generated or analyzed during this study are available in this research paper.
Code availability
The authors customized the NSGA-II algorithms for optimization. Code is available as per request.
References
Al-Amin M, Majdi AA-R, Rasel A, Rao TVVLN (2021) Multiple-objective optimization of hydroxyapatite-added EDM technique for processing of 316L-steel. Mater Manuf Process 36(4):1–14
Abdel-Fattah TM, Lofus D, Mahapatro A (2011) Nanosized controlled surface pretreatment of bio metallic alloy 316L stainless steel. J Biomed Nanotechnol 7:794–800
Al-Amin M, Majdi AA-R, Azeez AAA, Al’Hapis MAR, Hastuty S, Bryant MG (2020) Powder mixed-EDM for potential biomedical applications: a critical review. Mater Manuf Process 35(11):1789–1811
Al-Amin M, Majdi AA-R, Danish M, Harvey MT, Azeez AAA, Hastuty S, Fatema TZ, Bryant MG, Rubaiee S, Rao TVVLN (2020) Assessment of PM-EDM cycle factors influence on machining responses and surface properties of biomaterials: a comprehensive review. Precis Eng 66:531–549
Hanif M, Wasim A, Hakim AS, Sahar N, Sajid M, Nasir M (2019) Optimization of process parameters using graphene-based dielectric in electrical discharge machining of AISI D2 Steel. Int J Adv Manuf Technol 103:3735–3749
Al-Amin M, Majdi AA-R, Azeez AAA, Bryant MG, Danish M, Azlan A (2020) Bio-ceramic coatings adhesion and roughness of biomaterials through PM-EDM: a comprehensive review. Mater Manuf Process 35(11):1157–1180
Kunieda M, Lauwers B, Rajukar KP, Schumacher BM (2005) Advancing EDM through fundamental insight into the process. CIRP Ann 54:64–87
Jadam T, Santosh KS, Saurav D, Masanta M (2020) Powder-mixed electro-discharge machining performance of Inconel 718: effect of concentration of multi-walled carbon nanotube added to the dielectric media. Sadhana 45:135
Sachin M, Harmesh K (2017) Parametric optimization of multiwalled carbon nanotubes- assisted electrical discharge machining of Al-10%SiCp metal matrix composite by response surface methodology. Mater Manuf Process 32:263–273
Rajeswari R, Shunmugam MS (2020) Finishing performance of die-sink EDM with ultrasonic vibration and powder addition through pulse train studies. Mach Sci Technol 24:245–273
Sameehan SJ, Shravana K, Harpreet SA, Sundeep M, Narendra BD (2015) Amorphous coatings and surfaces on structural materials. Crit Rev Solid State Mater Sci 41:1–24
Azeez AAA, Majdi ABAR, Turnad LG, Prakash C, Eugen A, Al’Hapis MR, Sadaqat A (2017) A review of additive mixed-electric discharge machining: current status and future perspectives for surface modification of biomedical implants. Adv Mater Sci Eng:1–23
Talla G, Gangopadhayay S, Biswas CK (2016) State of the art in powder mixed electric discharge machining: a review. J Eng Manuf 224(11):1725–1739 0(0):1-16
Katsushi F, Hiromichi S, Masayuki S (2009) Influence of electrical conditions on performance of electrical discharge machining with powder suspended in working oil for titanium carbide deposition process. Int J Adv Manuf Technol 40:1093–1101
Kalyanmoy D, Amrit P, Sameer A, Meyarivan T (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6(2):1–16
Yusoff Y, Nagadiman MS, Zain AM (2011) Overview of NSGA-II for optimizing machining process parameters. Process Eng 15:3978–3983
Mitra K (2009) Multiobjective optimization of an industrial grinding operation under uncertainty. Chem Eng Sci 64(23):5043–5056
Seyed HRH, Shide SH, Edmundas KZ, Hadi A (2012) Extensions of LINMAP model for multi criteria decision making with grey numbers. Technol Econ Dev Econ 18(4):636–650
Yakup C, Fatih T (2020) An in-depth review of theory of the TOPSIS method: An experimental analysis. J Manag Anal 7(2):281–300
Mai C, Hong H, Huang S (2012) Advantages of carbon nanotubes in electrical discharge machining. Int J Adv Manuf Technol 59:111–117
Prabhu S, Vinayagan BK (2016) Optimization of carbon nanotubes based electrical discharge machining parameters using full factorial design and genetic algorithm. Aust J Mech Eng 14:161–173
Raymond M, Neeraj S, Kapil G, Paulo DJ (2019) Modeling and optimization of Wire-EDM parameters for machining of Ni55.8Ti shape memory alloy using hybrid approach of Taguchi and NSGA-II. Int J Adv Manuf Technol 102:1703–1717
Kamal K, Vijender S, Puneet K, Neeraj S (2019) EDM μ-drilling in Ti-6Al-7Nb: experimental investigation and optimization using NSGA-II. Int J Adv Manuf Technol 104:2727–2738
Emel K, Babur O (2013) Multi-objective optimization using Taguchi based grey relational analysis for micro-milling of Al 7075 material with ball nose end mill. Measurement 46:1849–1864
Eini S, Hamidreza S, Navid D, Moonyong L, Alireza B (2016) Multi-objective optimization of a cascade refrigeration system: exergetic, economic, environment, and inherent safety analysis. Appl Therm Eng 107:804–817
Kansal HK, Sehijpal S, Kumar P (2005) Parametric optimization of powder mixed electrical discharge machining by response surface methodology. J Mater Process Technol 169:427–436
Yubraj L, Gurpreet S, Amandeep SB, Prabin M, Purushottam K, Bikram T (2019) Surface modification of 316L SS with HAp nano-particles using PM-EDM for enhanced biocompatibility. Mater Today: Proceed 15:336–343
Mohammadzedeh MS, Noordin MY, Brusa E (2013) Role of multi-walled carbon nanotubes on the main parameters of the electrical discharge machining (EDM) process. Int J Adv Manuf Technol 68:1095–1102
Kamlesh P, Pramanik A, Chattopadhyaya S (2020) Machining performance of Inconel 718 using graphene nanofluid in EDM. Mater Manuf Process 35:3342
Kumar H (2014) Development of mirror like surface characteristics using nano powder mixed electric discharge machining (PMEDM). Int J Adv Manuf Technol 76:105–113
Kansal HK, Singh S, Kumar P (2007) Effect of silicon powder mixed EDM on machining rate of AISI D2 die steel. J Manuf Process 9:13–22
Pecas P, Henriques P (2003) Influence of silicon powder-mixed dielectric on conventional electrical discharge machining. Int J Mach Tools Manuf 43:1465–1471
Gurpreet S, Amandeep SB, Yubraj L, Prabin M, Purushottam K, Bikram T (2019) Machining performance and influence of process parameters on stainless steel 316L using die-sinker EDM with Cu tool. Mater Today: Proceed 18:2468–2476
Santosh K S, Saurav D (2018) Experimental studies on graphite powder-mixed elctro-discharge machining of Inconel 718 super alloys: comparison with conventional electro-discharge machining. J Process Mech Eng 0(0): 1-19.
Tan PC, Yeo SH (2011) Investigation of recast layers generated by a powder-mixed dielectric micro electrical discharge machining process. J Eng Manuf 225:1051–1062
Acknowledgements
Authors reveal their cordial gratefulness and admiration to Universiti Teknologi Petronas (UTP) for providing components and a working place.
Funding
The present research was fully assisted by the Ministry of Higher Education, Malaysia, through the FRGS fund-2020 (FRGS/1/2020/TK0/UTP/02/39; Cost center: 015MA0-132).
Author information
Authors and Affiliations
Contributions
Idea and design of the study: Md Al-Amin, Ahmad Majdi Abdul-Rani; Conducting of experiments: Md Al-Amin; Data acquisition: Md Al-Amin, Rasel Ahmed, Muhammad Danial Bin Abd Rani, and Muhammad Umair Shahid; Analysis of data: Md Al-Amin, Rasel Ahmed, and Fatema Tuj Zohura.
Drafting the manuscript: Md Al-Amin, Fatema Tuj Zohura; Revision of the manuscript thoroughly for important intellectual content: Md Al-Amin, Ahmad Majdi Abdul-Rani, Muhammad Umair Shahid.
Approval of the manuscript for publication: Ahmad Majdi Abdul-Rani, Md Al-Amin, Fatema Tuj Zohura, Rasel Ahmed, Muhammad Umair Shahid, and Muhammad Danial Bin Abd Rani.
Corresponding author
Ethics declarations
Ethics approval
Not Applicable
Consent to participate
All authors have willingly participated in this publication.
Consent to publish
The authors revised the manuscript critically and provided consent to publish.
Conflict of interest
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
Al-Amin, M., Abdul-Rani, A.M., Ahmed, R. et al. Multi-objective optimization of process variables for MWCNT-added electro-discharge machining of 316L steel. Int J Adv Manuf Technol 115, 179–198 (2021). https://doi.org/10.1007/s00170-021-07169-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00170-021-07169-1