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Supervised by Ministry of Industry and Information Technology of The People's Republic of China Sponsored by Harbin Institute of Technology Editor-in-chief Yu Zhou ISSNISSN 1005-9113 CNCN 23-1378/T

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Related citation:Ipsita Nayak,Jaydev Rana.Parametric Optimization of Wire-Electrical Discharge Machining Process on AISI D2 Tool Steel[J].Journal of Harbin Institute Of Technology(New Series),2025,32(5):94-104.DOI:10.11916/j.issn.1005-9113.2024055.
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Parametric Optimization of Wire-Electrical Discharge Machining Process on AISI D2 Tool Steel
Author NameAffiliation
Ipsita Nayak Department of Mechanical Engineering, Veer Surendra Sai University of Technology, Burla 768018, India 
Jaydev Rana Department of Mechanical Engineering, Veer Surendra Sai University of Technology, Burla 768018, India 
Abstract:
Wire-Electrical Discharge Machining (WEDM) process can create any complex contour in any conducting material, regardless of its strength or hardness, with higher accuracy. Present experimental investigation aims to determine suitable input process/machining parameters, e.g. pulse on time (T ON), peak current (IP), wire feed rate (WF), and pulse off time (TOFF), for optimizing the process performances, namely, cutting rate, kerf width, average roughness value of the machined surface, micro hardness, and surface crack density. Since four input parameters are considered in the present investigation, and each parameter is assumed to vary at three different levels (i.e. low, medium, high), the Taguchi L9 Orthogonal Array (OA) design approach has been used for the experimental purpose to enhance the process effiency. Similarly, a simple and popular multiresponse optimization approach, namely Grey Relational Analysis (GRA), is used to optimize five performance characteristics(output responses) simultaneously. The optimum process variables obtained are: TON of 110 μs, TOFFof 40 μs, IP of 10 A, and WF of 6 mm/min. These optimum process variables are validated with confirmatory experiment. The relative impact of input variables is determined using the Analysis of Variance (ANOVA) technique. Finally, correlations between individual outputs with different input parameters are established. This work will be helpful for industry personnel to use this machining process in a techno-economic way.
Key words:  WEDM  surface roughness  surface crack density  GRA  ANOVA  orthogonal array
DOI:10.11916/j.issn.1005-9113.2024055
Clc Number:TG5
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