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Experimental Study of MRR, TWR, SR on AISI D2 steel
Experimental Study of MRR, TWR, SR on AISI D2 steel
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Experimental Study of MRR, TWR, SR on AISI D2 steel
Experimental Study of MRR, TWR, SR on AISI D2 steel
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9,49 €
Research Paper (postgraduate) from the year 2016 in the subject Engineering - Mechanical Engineering, , language: English, abstract: This paper depicts the experimental study the input parameters of EDM i.e. current, pulse on time and pulse off time on output parameters material removal rate (MRR), tool wear rate (TWR) and surface roughness (SR). The workpiece materials selected was AISI D2. The aluminium used as tool electrode and EDM oil as dielectric fluid. Taguchi, method was used to perfor…

Experimental Study of MRR, TWR, SR on AISI D2 steel (e-book) (used book) | bookbook.eu

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Research Paper (postgraduate) from the year 2016 in the subject Engineering - Mechanical Engineering, , language: English, abstract: This paper depicts the experimental study the input parameters of EDM i.e. current, pulse on time and pulse off time on output parameters material removal rate (MRR), tool wear rate (TWR) and surface roughness (SR). The workpiece materials selected was AISI D2. The aluminium used as tool electrode and EDM oil as dielectric fluid. Taguchi, method was used to perform experiments, L9 orthogonal array was applied using MINITAB software. Signal to Noise (S/N) ratio and ANOVA were employed for parameter optimization and to achieve max MRR, min SR and TWR. The results indicate that the most prompting factor for MRR is Pulse off time. For TWR, the most influencing factor is current. For SR, the most prompting factor is pulse on time. Optimization is done by using Taguchi method on MINITAB 17 software.

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Research Paper (postgraduate) from the year 2016 in the subject Engineering - Mechanical Engineering, , language: English, abstract: This paper depicts the experimental study the input parameters of EDM i.e. current, pulse on time and pulse off time on output parameters material removal rate (MRR), tool wear rate (TWR) and surface roughness (SR). The workpiece materials selected was AISI D2. The aluminium used as tool electrode and EDM oil as dielectric fluid. Taguchi, method was used to perform experiments, L9 orthogonal array was applied using MINITAB software. Signal to Noise (S/N) ratio and ANOVA were employed for parameter optimization and to achieve max MRR, min SR and TWR. The results indicate that the most prompting factor for MRR is Pulse off time. For TWR, the most influencing factor is current. For SR, the most prompting factor is pulse on time. Optimization is done by using Taguchi method on MINITAB 17 software.

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