Response surface modelling and application of fuzzy grey relational analysis to optimise the multi response characteristics of EN-19 machined using powder mixed EDM

ABSTRACT

In the present manuscript, authors have made an attempt to find the effect of aluminium powder on the electric discharge machining (EDM) of EN-19 alloy steel. Brass metal is used as electrode material to conduct the experiments. The novelty of paper lies in machining of EN-19 steel using aluminium powder mixed EDM, which is not attempted so far. During experimentation, peak current, pulse on time, gap voltage and concentration of powder are considered as input process parameters for investigating their effect on material removal rate (MRR) and tool wear rate (TWR). Using the surface response modelling, a relationship has been established among the responses and process parameters in EDM. Optimisation of the machining parameters that are responsible for the best combination of MRR and TWR are determined with the help of fuzzy-grey relational analysis. Furthermore, the Micro structural and chemical composition analysis were characterised through Scanning Electron Microscope, Energy Dispersive Spectroscopy and X-Ray Diffraction, respectively.

Abbreviations: CCD: Central Composite Design; DF: Degree of Freedom; EDM: Electrical Discharge Machining; EDS: Energy Dispersive Spectroscopy; GRA: Grey Relational Analysis; GRC: Grey Relational Coefficients; GRG: Grey Relational Grade; MRR: Material Removal Rate; MS: Mean of Squares; PMEDM: Powder Mixed Electrical Discharge Machining; RSM: Response Surface methodology; SEM: Scanning Electron Microscope; SR: Surface Roughness; SS: Sum of Squares; TEM: Transmission electron microscopy; TWR: Tool Wear Rate; XRD: X- Ray Diffraction

KEYWORDS:

• Powder mixed EDM
• material removal rate
• tool wear rate
• fuzzy-grey relational analysis

Disclosure statement

No potential conflict of interest was reported by the authors.