Wire electrical discharge machining (wire-EDM) is an energy-intensive process, and its success relies on a correct selection of cutting parameters. It is vital to optimize energy consumption, along with productivity and quality. This experimental study optimized three parameters in wire-EDM:pulse-on time, servo voltage, and voltage concerning machining time, electric power, total energy consumption, surface roughness, and material removal rate. Two different plate thicknesses (15.88 mm and 25.4 mm) were machined. An orthogonal array, signalto-noise ratio, and means graphs, and an analysis of variance (ANOVA), determine the effects and contribution of cutting parameters on responses. Pulse-on time is the most significant factor for almost all variables, with a percentage of contribution higher than 50%. Multi-objective optimization is conducted to accomplish a concurrent decrease in all variables. A case study is proposed to compute carbon dioxide (CO2) tons and electricity cost in wire-EDM, using cutting parameters from multi-objective optimization and starting values commonly employed to cut that tool steel. A sustainable manufacturing approach reduced 5.91% of the electricity cost and CO2 tons when machining the thin plate, and these responses were diminished by 14.09% for the thicker plate. Therefore, it is possible to enhance the sustainability of the process without decreasing its productivity and quality.
The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-021-00353-2
Carmita Camposeco-Negrete
. Analysis and optimization of sustainable machining of AISI O1 tool steel by the wire-EDM process[J]. Advances in Manufacturing, 2021
, 9(2)
: 304
-317
.
DOI: 10.1007/s40436-021-00353-2
1. Devarajaiah D, Muthumari C (2018) Evaluation of power consumption and MRR in WEDM of Ti-6Al-4V alloy and its simultaneous optimization for sustainable production. J Braz Soc Mech Sci Eng 40:400-417
2. Garg A, Lam JSL (2016) Modeling multiple-response environmental and manufacturing characteristics of EDM process. J Clean Prod 137:1588-1601
3. Zhang Z, Yu H, Zhang Y et al (2018) Analysis and optimization of process energy consumption and environmental impact in electrical discharge machining of titanium superalloys. J Clean Prod 198:833-846
4. Salahi N, Jafari MA (2016) Energy-performance as a driver for optimal production planning. Appl Energy 174:88-100
5. U.S. Energy Information Administration (2011) Annual energy review 2011
6. Sharma S, Kumar VU, Bansal A (2020) Parametric optimization in wire EDM of D2 tool steel using Taguchi method. Mater Today Proc. https://doi.org/10.1016/j.matpr.2020.02.802
7. Zhang G, Li W, Zhang Y et al (2020) Analysis and reduction of process energy consumption and thermal deformation in a microstructure wire electrode electric discharge machining thin-wall component. J Clean Prod 244:118763. https://doi.org/10.1016/j.jclepro.2019.118763
8. Baroi BK, Debnath T, Jagadish Patowari PK (2020) Machinability assessment of titanium grade 2 alloy using deionized water in EDM. Mater Today Proc 26:2221-2225
9. Gowthaman PS, Gowthaman J, Nagasundaram N (2020) A study of machining characteristics of AISI 4340 alloy steel by wire electrical discharge machining process. Mater Today Proc. 27:565-570
10. Camposeco-Negrete C (2019) Prediction and optimization of machining time and surface roughness of AISI O1 tool steel in wire-cut EDM using robust design and desirability approach. Int J Adv Manuf Technol 103:2411-2422
11. Pramanik A, Basak AK (2018) Sustainability in wire electrical discharge machining of titanium alloy:understanding wire rupture. J Clean Prod 198:472-479
12. Majumder H, Maity K (2018) Prediction and optimization of surface roughness and micro-hardness using grnn and MOORAfuzzy-a MCDM approach for nitinol in WEDM. Measurement 118:1-13
13. Sonawane SA, Kulkarni ML (2018) Optimization of machining parameters of WEDM for Nimonic-75 alloy using principal component analysis integrated with Taguchi method. J King Saud Univ Eng Sci 30:250-258
14. Ramanan G, Dhas JER (2018) Multi objective optimization of wire EDM machining parameters for AA7075-PAC composite using grey:fuzzy technique. Mater Today Proc 5:8280-8289
15. Mouralova K, Kovar J, Klakurkova L et al (2018) Analysis of surface morphology and topography of pure aluminium machined using WEDM. Meas J Int Meas Confed 114:169-176
16. Udaya PJ, Jebarose JS, Pallavi P et al (2018) Optimization of wire EDM process parameters for machining hybrid composites (356/B4C/Fly Ash) using Taguchi technique. Mater Today Proc 5:7275-7283
17. Choudhuri B, Sen R, Kumar GS et al (2018) Modelling of surface roughness and tool consumption of WEDM and optimization of process parameters based on fuzzy-PSO. Mater Today Proc 5:7505-7514
18. Sen R, Choudhuri B, Barma JD et al (2018) Optimization of wire EDM parameters using teaching learning based algorithm during machining of maraging steel 300. Mater Today Proc 5:7541-7551
19. Sreenivasa RM, Venkata NBA, Venkaiah N (2018) Modified flower pollination algorithm to optimize WEDM parameters while machining Inconel-690 alloy. Mater Today Proc 5:7864-7872
20. Ishfaq K, Mufti NA, Mughal MP et al (2018) Investigation of wire electric discharge machining of stainless-clad steel for optimization of cutting speed. Int J Adv Manuf Technol 96:1429-1443
21. Kumar A, Soota T, Kumar J (2018) Optimization of wire-cut EDM process parameter by grey-based response surface methodology. J Ind Eng Int 14:821-829
22. Gamage JR, DeSilva AKM, Chantzis D et al (2017) Sustainable machining:process energy optimisation of wire electrodischarge machining of Inconel and titanium superalloys. J Clean Prod 164:642-651
23. Tejas AB, Mayur VP, Rajyalakshmi G (2017) WEDM machining on aerospace materials for improving material properties. Mater Today Proc 4:9107-9116
24. Singh V, Bhandari R, Yadav VK (2017) An experimental investigation on machining parameters of AISI D2 steel using WEDM. Int J Adv Manuf Technol 93:203-214
25. Manjaiah M, Laubscher RF, Kumar A et al (2016) Parametric optimization of MRR and surface roughness in wire electro discharge machining (WEDM) of D2 steel using Taguchi-based utility approach. Int J Mech Mater Eng 11:7-15
26. Maher I, Sarhan AAD, Barzani MM et al (2015) Increasing the productivity of the wire-cut electrical discharge machine associated with sustainable production. J Clean Prod 108:247-255
27. Shivade AS, Shinde VD (2014) Multi-objective optimization in WEDM of D3 tool steel using integrated approach of Taguchi method & grey relational analysis. J Ind Eng Int 10:149-162
28. Ming W, Shen F, Zhang G et al (2021) Green machining:a framework for optimization of cutting parameters to minimize energy consumption and exhaust emissions during electrical discharge machining of Al 6061 and SKD 11. J Clean Prod 285:124889. https://doi.org/10.1016/j.jclepro.2020.124889
29. Jagadish RA (2016) Optimization of process parameters of green electrical discharge machining using principal component analysis (PCA). Int J Adv Manuf Technol 87:1299-1311
30. Wang X, Chen L, Dan B et al (2018) Evaluation of EDM process for green manufacturing. Int J Adv Manuf Technol 94:633-641
31. Zhang Y, Zhang Z, Zhang G et al (2020) Reduction of energy consumption and thermal deformation in WEDM by magnetic field assisted technology. Int J Precis Eng Manuf Green Technol 7:391-404
32. Gao M, Wang Q, Li L et al (2019) Comprehensive energy-saving method for sheet metal forming. Int J Adv Manuf Technol 104:2273-2285
33. Bourithis L, Papadimitriou GD, Sideris J (2006) Comparison of wear properties of tool steels AISI D2 and O1 with the same hardness. Tribol Int 39:479-489
34. Kumar S, Maity SR, Patnaik L (2020) Effect of heat treatment and TiN coating on AISI O1 cold work tool steel. Mater Today Proc 26:685-688
35. Zheng J, Zheng W, Chen A et al (2020) Sustainability of unconventional machining industry considering impact factors and reduction methods of energy consumption:a review and analysis. Sci Total Environ 722:137897. https://doi.org/10.1016/j.scitotenv.2020.137897
36. Sodick Inc (2012) Wire EDM machine operation training for LN1W/LN2W control. http://fab.cba.mit.edu/content/tools/sodick_edm/sodick_user_manual_small.pdf. Accessed 31 Oct 2019
37. Edem IF, Mativenga PT (2017) Modelling of energy demand from computer numerical control (CNC) toolpaths. J Clean Prod 157:310-321
38. Fluke-Direct.com Fluke 43B/003 Power quality analyzer. In:Fluke 43B/003 Power Qual. Anal.
39. Misra JP, Danish M, Prateek et al (2018) Effect of wire related parameters and servo feed on process performance characteristics during WEDM of combustor material. In:IOP conference series:materials science and engineering. https://doi.org/10.1088/1757-899X/402/1/012165
40. Ekici E, Motorcu AR, Kuş A (2016) Evaluation of surface roughness and material removal rate in the wire electrical discharge machining of Al/B4C composites via the Taguchi method. J Compos Mater 50:2575-2586
41. Fard RK, Afza RA, Teimouri R (2013) Experimental investigation, intelligent modeling and multi-characteristics optimization of dry WEDM process of Al-SiC metal matrix composite. J Manuf Process 15:483-494
42. Kumar R, Choudhury SK (2011) Prevention of wire breakage in wire EDM. Int J Mach Mach Mater 9:86-102
43. Kumar H, Manna A, Kumar R (2018) Modeling of process parameters for surface roughness and analysis of machined surface in WEDM of Al/SiC-MMC. Trans Indian Inst Met 71:231-244
44. Sen R, Choudhuri B, Barma JD et al (2018) Study the impact of process parameters and electrode material on wire electric discharge machining performances. Mater Today Proc 5:7552-7560
45. Yan H, Bakadiasa KD, Yan Z et al (2020) Sustainable production of high-uniformity workpiece surface quality in wire electrical discharge machining by fabricating surface microstructure on wire electrode. J Clean Prod 259:120881. https://doi.org/10.1016/j.jclepro.2020.120881
46. United States Bureau of Labor Statistics (2019) Machinists and tool and die makers. In:Occup. Outlook Handb
47. United States Environmental Protection Agency (2018) Greenhouse gases equivalencies calculator:calculations and references
48. United States Energy Information Administration (2020) Average price of electricity to ultimate customers by end-use sector. https://www.eia.gov/electricity/monthly/epm_table_grapher.php?t=epmt_5_6_a. Accessed 5 Jan 2021
