In any manufacturing process, optimization of process parameters is the key step in producing hig... more In any manufacturing process, optimization of process parameters is the key step in producing high quality parts without cost inflation. Multi-criteria optimization of processes parameters could be used to simultaneously achieve several conflicting goals such as increasing product quality and reducing production time. In this paper grey relational analysis (GRA) and Taguchi method have been employed to optimize Electrical Discharge Machining (EDM) process parameters for AISI 2312 (40CrMnMoS86) hot worked steel alloy. The experimental data are gathered based on Taguchi L 36 design matrix. The tests are conducted under varying peak current (I), voltage (V), pulse on time (T on), pulse off time (T off) and duty factor (η). The process output characteristics include surface roughness (SR), tool wear rate (TWR) and material removal rate (MRR). The objective is to find a combination of process parameters to minimize TWR and SR and maximize MRR. The three performance characteristics are combined into a single objective using grey relational analysis. The GRA was followed by the signal to noise ratio to specify the optimal levels of process parameters. The significance of the process parameters on the overall quality characteristics of the EDM process was also evaluated quantitatively using the analysis of variance (ANOVA) method. Optimal results were verified through additional experiments.
In this paper Taguchi method has been employed to optimize Electrical Discharge Machining (EDM) p... more In this paper Taguchi method has been employed to optimize Electrical Discharge Machining (EDM) process for 40CrMnMoS86 hot worked steel parts. The experimental data are gathered based on Taguchi L36 design matrix. The tests are conducted under varying peak current (I), voltage (V), pulse on time (Ton), pulse off time (Toff) and duty factor (). The effects of these input parameters are then determined on three important process output responses, namely; Surface Roughness (SR), Tool Wear Rate (TWR) and Material Removal Rate (MRR). Using these data and signal-to-noise (S/N) ratio analysis, the process parameters can be set to achieve desired surface roughness, tool wear and material removal rates. Next, analysis of variance (ANOVA) and F–test have been used to evaluate the relative significance of process variables affecting process outputs. A set of verification tests is also performed to verify the accuracy of optimization procedure in determining the optimal levels of machining pa...
In any manufacturing process, optimization of process parameters is the key step in producing hig... more In any manufacturing process, optimization of process parameters is the key step in producing high quality parts without cost inflation. Multi-criteria optimization of processes parameters could be used to simultaneously achieve several conflicting goals such as increasing product quality and reducing production time. In this paper grey relational analysis (GRA) and Taguchi method have been employed to optimize Electrical Discharge Machining (EDM) process parameters for AISI 2312 (40CrMnMoS86) hot worked steel alloy. The experimental data are gathered based on Taguchi L 36 design matrix. The tests are conducted under varying peak current (I), voltage (V), pulse on time (T on), pulse off time (T off) and duty factor (η). The process output characteristics include surface roughness (SR), tool wear rate (TWR) and material removal rate (MRR). The objective is to find a combination of process parameters to minimize TWR and SR and maximize MRR. The three performance characteristics are combined into a single objective using grey relational analysis. The GRA was followed by the signal to noise ratio to specify the optimal levels of process parameters. The significance of the process parameters on the overall quality characteristics of the EDM process was also evaluated quantitatively using the analysis of variance (ANOVA) method. Optimal results were verified through additional experiments.
In this paper Taguchi method has been employed to optimize Electrical Discharge Machining (EDM) p... more In this paper Taguchi method has been employed to optimize Electrical Discharge Machining (EDM) process for 40CrMnMoS86 hot worked steel parts. The experimental data are gathered based on Taguchi L36 design matrix. The tests are conducted under varying peak current (I), voltage (V), pulse on time (Ton), pulse off time (Toff) and duty factor (). The effects of these input parameters are then determined on three important process output responses, namely; Surface Roughness (SR), Tool Wear Rate (TWR) and Material Removal Rate (MRR). Using these data and signal-to-noise (S/N) ratio analysis, the process parameters can be set to achieve desired surface roughness, tool wear and material removal rates. Next, analysis of variance (ANOVA) and F–test have been used to evaluate the relative significance of process variables affecting process outputs. A set of verification tests is also performed to verify the accuracy of optimization procedure in determining the optimal levels of machining pa...
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