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Performance evaluation and multi-objective optimization of EDM parameters for Ti6Al4V using different tool

Manoj Jagdale¹, Masuk Abdullah², Nitin Ambhore³

¹Department of Mechanical Engineering, Vishwakarma Institute of Information Technology, Savitribai Phule Pune University (SPPU), Pune, 411048, India.

Scientific Reports

|August 18, 2025

Summary

This summary is machine-generated.

Graphite electrodes offer superior performance in Electrical Discharge Machining (EDM) of Ti6Al4V alloy, achieving high material removal rates and low tool wear. The Teaching-Learning-Based Optimization (TLBO) algorithm effectively optimizes EDM parameters for this difficult-to-cut material.

Keywords:

Brass tool Copper tool Electrical discharge machining Graphite tool Optimization Ti6Al4V alloy

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Area of Science:

Materials Science
Manufacturing Engineering

Background:

Ti6Al4V alloy is crucial in aerospace and biomedical fields but challenging to machine due to its poor machinability.
Electrical Discharge Machining (EDM) is a viable non-conventional method for processing difficult-to-cut materials like Ti6Al4V.
Tool electrode material and process parameters significantly impact EDM efficiency and outcomes.

Purpose of the Study:

To experimentally investigate the influence of graphite, copper, and brass electrodes on the EDM performance of Ti6Al4V alloy.
To optimize key EDM parameters (pulse-on time, pulse-off time, current) for Ti6Al4V machining.
To evaluate and compare the effectiveness of the Teaching-Learning-Based Optimization (TLBO) algorithm in optimizing EDM.

Main Methods:

Experimental design using Taguchi's L9 orthogonal array.
Analysis of Variance (ANOVA) to determine factor significance.
Optimization of material removal rate (MRR), tool wear rate (TWR), surface roughness (SR), and dimensional deviation (DD) using the TLBO algorithm.
Scanning Electron Microscopy (SEM) for surface morphology analysis.

Main Results:

Graphite electrodes yielded the highest MRR (31.03 mm³/min), lowest TWR (0.4648 mm³/min), and minimal dimensional deviation (101.76 μm).
Brass electrodes resulted in the smoothest surface finish (SR = 3.19 μm).
TLBO algorithm demonstrated good agreement between predicted and experimental results, validating its optimization capability.
SEM analysis confirmed superior surface integrity with graphite electrodes.

Conclusions:

Graphite is the most effective electrode material for optimizing MRR, TWR, and DD in EDM of Ti6Al4V.
The TLBO algorithm is a robust tool for optimizing complex machining processes like EDM.
Findings provide practical insights for selecting electrodes and parameters for efficient Ti6Al4V machining.