Grey Relational Analysis-Based Multi-Response Optimization of Magnetic-Field-Assisted Powder-Mixed Electric Discharge Machining of Inconel 706

Autor: Sushil Kumar, Mudimallana Goud, Narendra Mohan Suri
Rok vydání: 2021
Předmět:
Zdroj: Arabian Journal for Science and Engineering. 47:8315-8339
ISSN: 2191-4281
2193-567X
DOI: 10.1007/s13369-021-06204-3
Popis: In the current study, an experimental investigation has been done using the hybrid magnetic-field-assisted powder-mixed electric discharge machining (MFAPMEDM) technique to enhance the process performance while machining Inconel 706 superalloy. Inconel 706 is a newly developed superalloy for aircraft applications. All the experimentation work was done according to Taguchi’s L9 orthogonal array (OA) to analyse the effect of controlled input parameters like peak current (Ip), pulse ‘ON’ (Pon) and pulse ‘OFF’ (Poff) duration on response parameters. Material removal rate (MRR), tool wear rate (TWR) and surface roughness (Ra) were selected as response parameters, and further multi-response optimization was done through grey relational analysis (GRA). GRA results revealed that Pon (62.84%) is the most influential input variable followed by Ip (28.64%) and Poff (8.50%) for controlling all the responses simultaneously. GRA optimized parameters were determined as Ip (5 A), Pon (50 µs) and Poff (20 µs). The surface morphology of the tool (cathode) and workpiece (anode) was assessed using field emission scanning electron microscopy (FESEM), which revealed the presence of partially melted crater boundaries/debris, micro-holes and debris on the surface. The results presented in this paper will help future researchers in studying the machining characteristics of the Inconel 706 superalloy.
Databáze: OpenAIRE
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