Modelling Approach for the Prediction of Machinability in Al6061 Composites by Electrical Discharge Machining

Hariharan Sree Ram,Marimuthu Uthayakumar,Sundaresan Thirumalai Kumaran,Shanmugam Suresh Kumar,Kinga Korniejenko

doi:10.3390/app12052673

Hariharan Sree Ram, Marimuthu Uthayakumar + Show 3 more

Open Access

https://doi.org/10.3390/app12052673

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Abstract

This work aims to identify the pattern for the major output parameters, material removal rate (MRR) and surface roughness (Ra) of different combinations of Al6061-based composites. Based on the verification carried out on these patterns using analysis of variance (ANOVA) as the mathematical tool, the work predicts the mentioned output characteristics while machining Al6061 composites of different material compositions based on their hardness values. ANOVA was employed for the generation of equations of the particular composite. The equations were compared for the coefficients of each parameter employed in ANOVA. The work was carried out comparing the characteristic equation of different combinations of Al6061-based composite. The results indicate that the coefficients of the current show a drastic variation when compared to other coefficients for both the output parameters. It was observed that the current and its coefficients contribute to the output parameters based on the variation in hardness. For surface roughness, the constant of the characteristic equation was also found to influence the parameter for the change in hardness. The equation derived for both material removal rate (MRR) and surface roughness (Ra) were identified to be matching with the experimental result carried out for validation. The average variation observed was 9.3% for MRR and 7.2% for surface roughness.

Highlights

The requirement of improved strength-to-weight ratio materials has led to the introduction of composite materials in many applications such as structural, automotive, space, manufacturing, etc
It was observed in the work that the addition of 12% silicon carbide (SiC) as the reinforcement increased hardness by 50% and tensile strength by 60%, whereas the addition of the same percentage of graphite reduced the hardness by 25% but increased the tensile strength by 60%
The results indicate that the variations observed using the FEA showed 20% variation and the genetic-algorithm-based mathematical model showed a variation in the range of 10%

Summary

Introduction

The requirement of improved strength-to-weight ratio materials has led to the introduction of composite materials in many applications such as structural, automotive, space, manufacturing, etc. The work identifies current and pulse-on time as the major parameters contributing to MRR and surface roughness. The work aimed at optimizing the kerf width, surface roughness and cutting rate based on the input parameters of current, voltage and pulse-on time. This algorithm, once developed, can provide a proper optimised condition for the specified input parameters. This work aims to provide a prediction of the different output parameters based on the experimental values obtained by Singh [16], Raza [15], Murugesan [2] and Nataraj [1] in the machining of different combinations of Al6061 composites and to compare the mathematical models to identify and predict the output parameters based on the variation of these parameters. To verify the derived equations by carrying out experiments on Al6061-1% SiC MMC and comparing the model results with the experimental results

Materials

Methodology

Validation

Surface Topography

Findings

Future Work