Integrating soft computing approach to optimize and predict powder mixed wire electric discharge machinability characteristics of PBLF-Ti-6Al-4V alloy

This study focuses on optimizing Powder Mixed Wire Electric Discharge Machining of titanium alloy Ti-6Al-4V using zinc, molybdenum disulfide, and carbon nanotubes as dielectric additives. Experiments were designed using Taguchi’s method with analysis of variance to examine the effects of discharge current, pulse on time, gap voltage, and powder concentration on material removal rate, surface roughness, and microhardness. The comparative evaluation of different dielectric powders highlights their distinct roles in improving machining efficiency. The minimum wire weight loss of 0.0049 milligrams per minute was achieved with one gram per litre of zinc, a discharge current of four amperes, a gap voltage of ninety volts, a pulse on time of three hundred milliseconds, and a pulse off time of twenty-five milliseconds. Molybdenum disulfide at one gram per litre produced the highest microhardness of three hundred and sixty-eight Vickers under optimized conditions of four amperes discharge current, one hundred and ten volts gap voltage, two hundred milliseconds pulse on time, and fifty milliseconds pulse off time. Discharge current was found to have the greatest influence on material removal rate, followed by powder concentration. The study provides valuable insights into enhancing machining precision and achieving high-quality performance in titanium alloy applications.

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Publication Details

Journal
Cogent Engineering
Published
2025-10-17
DOI
https://doi.org/10.1080/23311916.2025.2572292
Primary Topic
Advanced Machining and Optimization Techniques
Type
article
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article

Integrating soft computing approach to optimize and predict powder mixed wire electric discharge machinability characteristics of PBLF-Ti-6Al-4V alloy

Raviraj Shetty, Adithya Hegde, J P Supriya, Rajesh Nayak et al.
Cogent Engineering
Advanced Machining and Optimization Techniques
article

Integrating soft computing approach to optimize and predict powder mixed wire electric discharge machinability characteristics of PBLF-Ti-6Al-4V alloy

Raviraj Shetty, Adithya Hegde, J P Supriya, Rajesh Nayak, Gururaj Bolar
article en

Abstract

This study focuses on optimizing Powder Mixed Wire Electric Discharge Machining of titanium alloy Ti-6Al-4V using zinc, molybdenum disulfide, and carbon nanotubes as dielectric additives. Experiments were designed using Taguchi’s method with analysis of variance to examine the effects of discharge current, pulse on time, gap voltage, and powder concentration on material removal rate, surface roughness, and microhardness. The comparative evaluation of different dielectric powders highlights their distinct roles in improving machining efficiency. The minimum wire weight loss of 0.0049 milligrams per minute was achieved with one gram per litre of zinc, a discharge current of four amperes, a gap voltage of ninety volts, a pulse on time of three hundred milliseconds, and a pulse off time of twenty-five milliseconds. Molybdenum disulfide at one gram per litre produced the highest microhardness of three hundred and sixty-eight Vickers under optimized conditions of four amperes discharge current, one hundred and ten volts gap voltage, two hundred milliseconds pulse on time, and fifty milliseconds pulse off time. Discharge current was found to have the greatest influence on material removal rate, followed by powder concentration. The study provides valuable insights into enhancing machining precision and achieving high-quality performance in titanium alloy applications.

Cogent EngineeringVol. 12(1)
Manipal Academy of Higher Education (IN)
Openalex Percentile: Top 71%
Advanced Machining and Optimization Techniques
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Integrating soft computing approach to optimize and predict powder mixed wire electric discharge machinability characteristics of PBLF-Ti-6Al-4V alloy — Raviraj Shetty, Adithya Hegde, et al. · Cogent Engineering (2025) | TGRS Research Map | TGRS