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Optimization and Regression Modeling of Wire Electrical Discharge Machining for Cupronickel Material Mohan Babu University

SAE Technical Papers (1906-current) Available online

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Format:
Book
Conference/Event
Author/Creator:
Natarajan, Manikandan, author.
Contributor:
A, Gnanarathinam
D, Palanisamy
Pasupuleti, Thejasree
Silambarasan, R.
Umapathi, D.
Conference Name:
11th SAEINDIA International Mobility Conference (SIIMC 2024) (2024-12-11 : New Delhi, India)
Language:
English
Physical Description:
1 online resource cm
Place of Publication:
Warrendale, PA SAE International 2024
Summary:
Wire Electrical Discharge Machining (WEDM) is a highly accurate machining method that is well-known for its capacity to create complex forms in conductive materials with exceptional precision. Cupronickel, a hard material consisting of copper, nickel, and additional components, is widely employed in marine, automotive, and electrical engineering fields because of its exceptional ability to resist corrosion and conduct heat. The intention of this study is to optimize the parameters of Wire Electrical Discharge Machining (WEDM) for Cupronickel material and create regression models to accurately forecast the performance of the machining process. An exploration was carried out to analyze the influence of important parameters in wire electrical discharge machining (WEDM), namely pulse-on time, pulse-off time, and applied current on key performance indicators such as material removal rate (MRR), surface roughness (Ra). The methodology of design of experiments (DOE) enabled a systematic exploration of parameters. Regression models were created using statistical methods to ascertain the connections between process parameters and performance indicators. These models offer a prognostic tool for optimizing WEDM parameters and attaining desired machining results. The results exhibited the efficacy of the regression models in accurately forecasting the machining performance for Cupronickel material. The models provide valuable insights into the most effective parameter configurations for maximizing machining efficiency and surface quality. Manufacturers can improve machining productivity and quality in precision engineering applications by utilizing regression models, thereby facilitating the wider implementation of WEDM technology
Notes:
Vendor supplied data
Publisher Number:
2024-28-0244
Access Restriction:
Restricted for use by site license

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