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Title: | Investigation of the WEDM of Al/B4C/Gr reinforced hybrid composites using the Taguchi method and response surface methodology |
Authors: | Motorcu, Ali Rıza Ekici, Ergün Uludağ Üniversitesi/Teknik Bilimler Meslek Yüksekokulu/Makine Programı Bölümü. Kuş, Abdil AAG-9412-2021 57196667786 |
Keywords: | Materials science Al/B4C/Gr hybrid composite Material removal rate Surface roughness Taguchi method Wire electrical discharge machining Metal-matrix composites Wire-edm Parameters Optimization Machinability Wear Rsm Performance Roughness Aluminum Electric discharge machining Electric discharges Hybrid materials Surface properties Surface roughness Taguchi methods Wire Correlation coefficient Effective parameters Hybrid composites Machining parameters Response surface methodology Surface roughness (Ra) Wire electrical discharge machining Analysis of variance (ANOVA) |
Issue Date: | 6-Oct-2014 |
Publisher: | De Gruyter Poland |
Citation: | Motorcu, A. R. vd. (2016). "Investigation of the WEDM of Al/B4C/Gr reinforced hybrid composites using the Taguchi method and response surface methodology". Science and Engineering of Composite Materials, 23(4), 435-445. |
Abstract: | In this study, the effects of machining parameters on the material removal rate (MRR) and surface roughness (Ra) were investigated during the cutting of Al/B4C/Gr hybrid composites by wire electrical discharge machining (WEDM). Wire speed (W-S), pulse-on time (T-on) and pulse-off time (T-off) were chosen as the control factors. The L-27 (3(3)) orthogonal array in the Taguchi method was used in the experimental design and for the determination of optimum control factors. Response surface methodology was also used to determine interactions among the control factors. Variance analysis (ANOVA) was applied in the determination of the effects of control factors on the MRR and Ra. According to the ANOVA results, the most effective parameters on MRR and Ra were wire speed with a 85.94% contribution ratio, and pulse-on-time with a 47.7% contribution ratio. The optimum levels of the control factors for MRR and Ra were determined as A(3)B(3)C(3) and A(1)B(1)C(2). In addition, second-order predictive models were developed for MRR and Ra; correlation coefficients (R-2) were calculated as 0.992 and 0.63. |
URI: | https://doi.org/10.1515/secm-2014-0063 https://www.degruyter.com/document/doi/10.1515/secm-2014-0063/html http://hdl.handle.net/11452/29853 |
ISSN: | 0792-1233 2191-0359 |
Appears in Collections: | Scopus Web of Science |
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