| Abstrakt: |
Wire electrical discharge machining (WEDM) is one of the advanced unconventional machining processes (UCMP) used for machining harder earth materials such as Die steels and Mold steels. Because of this specific advantage of WEDM, researchers are still looking for various ways to improve this process. However, from numerous studies, it was found that achieving a good surface roughness (SR), Material removal rate (MRR), Tool wear rate (TWR) and cutting speed is still a challenge in the WEDM process. It is because of the workpiece material's excess hardness, such as AISI P20. Therefore, in this present study, we investigate, analyze and optimize the cutting parameters of harder materials using a specific WEDM tool and machine. After going through several types of research, it was found that the AISI P20 + Ni (DIN 1.2738 is one of the harder earth materials and has numerous industrial applications). It is chosen as the workpiece material and cryogenically treated Zinc-coated brass wire as a Tool wire material to study and optimize Material removal rate and minimize wire damages and wear. To determine the experimental behaviors of the selected AISI P20 + Ni workpiece material using cryogenic treated Zinc-coated brass wire as a tool, up to 27 experimental runs have been performed on an eNOVA Electronic CNC WEDM machine. The output parameters MRR, SR, Wire consumption (WC) and kerf width are noted by changing the input parameters Pulse ON/OFF time, Peak current and Servo voltage. In addition, Response surface methodology (RSM) and Hybrid Deep belief neural network based Search and Rescue optimization (DBN based SAR) are introduced to verify the significance of output parameters and achieve the optimized output. As a result, respective output values achieved as MRR = 2.71943 mm3/min, SR = 3.27194 µm, WC = 0.0208325 kg, and kerf width = 0.26932 mm for the input parameters pulse off time 60 µs, pulse on time 110 µs, servo voltage 5.1869 V, peak current 11.00889 A, while the desirability will be 0.790 for the optimized parameters. [ABSTRACT FROM AUTHOR] |
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