Parametric Optimization of WEDM Process for AISI 1026 Steel Using Taguchi-TOPSIS Hybrid Method

Abstract

In this research, holes were created in a mild steel AISI 1026 work piece using a Wire EDM (Electrical Discharge Machining) machine. The goal was to evaluate and look at the machined holes\' quality characteristics. The control parameters of Wire Electrical Discharge Machining (WEDM) like voltage, pulse-on time, and pulse-off time have been taken into consideration in this work. Surface Roughness (SR) and Material Removal Rate (MRR) have been considered in the assessment of the quality characteristics. The Taguchi L9 orthogonal array was used to set the control settings at different levels during the experiments. Present research has established rankings on various experimental sets by using the TOPSIS approach for combined response analysis. Optimal parameter settings were found using the Signal-to-Noise (S/N) ratio. The research showed that voltage at level 1, pulse on time at level 1, and pulse off time at level 3 were the optimal parameters. The most significant factor was determined using ANOVA, and Pulse on Time provided the highest proportion (60.27%). The performance index is calculated using the regression equation, which also shows the relationship between the machine\'s control variables and performance index. The S/N ratio value of -0.8569 obtained in the confirmation test, that shows successful implementation of the Taguchi-TOPSIS approach.

Introduction

Wire Electrical Discharge Machining (WEDM) is a non-contact precision machining process that uses a continuously fed, electrically charged wire to erode hard and conductive materials into complex shapes with high accuracy. Because it produces minimal thermal and mechanical stress, WEDM is widely used in aerospace, medical, tool-making, and other high-precision industries. Compared to conventional machining, it offers tight tolerances, fine surface finish, and the ability to machine difficult-to-cut materials.

The literature review highlights extensive research on optimizing EDM and WEDM process parameters to improve material removal rate (MRR), surface roughness (SR), dimensional accuracy, and tool wear. Various optimization and modeling techniques have been applied, including Taguchi methods, Grey Relational Analysis (GRA), ANOVA, Response Surface Methodology (RSM), Artificial Neural Networks (ANN), Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Fuzzy logic, TOPSIS, PCA, and hybrid approaches. Most studies identify discharge current, pulse-on time, pulse-off time, voltage, and wire feed rate as critical parameters influencing machining performance. Advanced methods such as ANN, SVR, and hybrid multi-objective optimization techniques have shown superior prediction accuracy and optimization efficiency.

The experimental plan focuses on optimizing WEDM parameters for machining AISI 1026 mild steel to achieve improved surface roughness, material removal rate, and dimensional accuracy. Brass-coated copper wire is used, and voltage, pulse-on time, and pulse-off time are selected as input parameters at three levels. Taguchi methodology is applied for experimental design, with signal-to-noise ratio analysis and ANOVA used to evaluate parameter significance. Additionally, the TOPSIS method is employed for multi-criteria decision-making to identify optimal machining conditions.

Conclusion

The study found that applying the Taguchi-TOPSIS technique to optimise WEDM process parameters for AISI 1026 mild steel is successful and results in notable performance gains. Surface roughness and material removal rate were combined into a single composite response using TOPSIS. With a performance ratio of -0.9012 and the highest score, Experiment No. 8 came in first place. The ideal parameters were voltage level 1, pulse-on time level 1, and pulse-off time level 3, according to Signal-to-Noise (S/N) ratios. The percentage contribution of each parameter was calculated using ANOVA. To forecast performance index values, a regression equation was created. The efficacy of the approach was confirmed by confirmation tests with 30 V, 6 µs pulse-on time, and 60 µs pulse-off duration, which produced an S/N ratio of -0.8569. Data Availability Statement The authors confirm that the data supporting the findings of this study are available within the article. Disclosures and declarations 1. Funding: This research received no external funding. 2. Conflicts of Interest: The authors declare no conflict of interest.

References

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Copyright

Copyright © 2026 Vaishali Shandily, Jyoti Vimal, Vedansh Chaturvedi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.