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Multi-Response Optimization of Al/GrCp10 MMC Performance in WEDM Using Integrated TOPSIS-ANFIS Approach
https://orcid.org/http://orcid.org/0000-0003-1103-2190
https://orcid.org/http://orcid.org/0000-0003-3739-5360
https://orcid.org/http://orcid.org/0000-0003-3721-9164
Lightweight material such as aluminum-based metal matrix composites (MMC) is extensively used in automobile, aerospace, and some other precise engineering applications. For such material, the processing is not simple due to the presence of some other material in the aluminum. To overcome this, wire electrical discharge machining (WEDM) is projected for cutting of aluminum–graphite (10%) metal matrix composite with variation in process parameters. In present work, the technique for order of preference by similarity to ideal solution (TOPSIS) and an adaptive neuro-fuzzy inference system (ANFIS) is employed to assess the WEDM of AlGrCp10 MMC. Taguchi’s L27 orthogonal array was adopted for the experimentation. The influence of process variables, pulse on time (PON), pulse off time (POFF), the feed rate of wire (WFR), and the tension in the wire (WT), is considered for overall performance measure. The overall performance is measured in terms of the responses such as material removal rate (MRR), overcut (OVT), and surface roughness (Ra). Analysis of variance, i.e., ANOVA, is performed to find out the most influencing process parameters. TOPSIS-ANFIS predicted results are tested for the confirmation tests which show an enhancement of overall closeness coefficient increases from 0.656793 to 0.772138. The optimum setting obtained for the overall performance is pulse on time = 112 μs pulse off time = 56 μs, wire feed rate = 12 m/min, and wire tension of 1.2 kg.
Multi-Response Optimization of Al/GrCp10 MMC Performance in WEDM Using Integrated TOPSIS-ANFIS Approach
https://orcid.org/http://orcid.org/0000-0003-1103-2190
https://orcid.org/http://orcid.org/0000-0003-3739-5360
https://orcid.org/http://orcid.org/0000-0003-3721-9164
Lightweight material such as aluminum-based metal matrix composites (MMC) is extensively used in automobile, aerospace, and some other precise engineering applications. For such material, the processing is not simple due to the presence of some other material in the aluminum. To overcome this, wire electrical discharge machining (WEDM) is projected for cutting of aluminum–graphite (10%) metal matrix composite with variation in process parameters. In present work, the technique for order of preference by similarity to ideal solution (TOPSIS) and an adaptive neuro-fuzzy inference system (ANFIS) is employed to assess the WEDM of AlGrCp10 MMC. Taguchi’s L27 orthogonal array was adopted for the experimentation. The influence of process variables, pulse on time (PON), pulse off time (POFF), the feed rate of wire (WFR), and the tension in the wire (WT), is considered for overall performance measure. The overall performance is measured in terms of the responses such as material removal rate (MRR), overcut (OVT), and surface roughness (Ra). Analysis of variance, i.e., ANOVA, is performed to find out the most influencing process parameters. TOPSIS-ANFIS predicted results are tested for the confirmation tests which show an enhancement of overall closeness coefficient increases from 0.656793 to 0.772138. The optimum setting obtained for the overall performance is pulse on time = 112 μs pulse off time = 56 μs, wire feed rate = 12 m/min, and wire tension of 1.2 kg.
Multi-Response Optimization of Al/GrCp10 MMC Performance in WEDM Using Integrated TOPSIS-ANFIS Approach
https://orcid.org/http://orcid.org/0000-0003-1103-2190
https://orcid.org/http://orcid.org/0000-0003-3739-5360
https://orcid.org/http://orcid.org/0000-0003-3721-9164
Lightweight material such as aluminum-based metal matrix composites (MMC) is extensively used in automobile, aerospace, and some other precise engineering applications. For such material, the processing is not simple due to the presence of some other material in the aluminum. To overcome this, wire electrical discharge machining (WEDM) is projected for cutting of aluminum–graphite (10%) metal matrix composite with variation in process parameters. In present work, the technique for order of preference by similarity to ideal solution (TOPSIS) and an adaptive neuro-fuzzy inference system (ANFIS) is employed to assess the WEDM of AlGrCp10 MMC. Taguchi’s L27 orthogonal array was adopted for the experimentation. The influence of process variables, pulse on time (PON), pulse off time (POFF), the feed rate of wire (WFR), and the tension in the wire (WT), is considered for overall performance measure. The overall performance is measured in terms of the responses such as material removal rate (MRR), overcut (OVT), and surface roughness (Ra). Analysis of variance, i.e., ANOVA, is performed to find out the most influencing process parameters. TOPSIS-ANFIS predicted results are tested for the confirmation tests which show an enhancement of overall closeness coefficient increases from 0.656793 to 0.772138. The optimum setting obtained for the overall performance is pulse on time = 112 μs pulse off time = 56 μs, wire feed rate = 12 m/min, and wire tension of 1.2 kg.
Multi-Response Optimization of Al/GrCp10 MMC Performance in WEDM Using Integrated TOPSIS-ANFIS Approach
J. Inst. Eng. India Ser. D
Phate, Mangesh (author) / Toney, Shraddha (author) / Phate, Vikas (author) / Tatwawadi, Vivek (author)
Journal of The Institution of Engineers (India): Series D ; 103 ; 249-261
2022-06-01
13 pages
Article (Journal)
Electronic Resource
English
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