Comparative Study of Cryogenic and Non-Cryogenic Zinc-Coated Brass Electrodes in WEDM of D3 Tool Steel Using GRA-ANFIS Optimization

Abstract

Surface integrity and dimensional precision are critical in aerospace cold-work tooling, where AS9100 standards demand defect-free surfaces to prevent fatigue failure under cyclic loading. While Wire Electrical Discharge Machining (WEDM) is essential for profiling high-hardness alloys like AISI D3 tool steel (58–63 HRC), the process inherently generates a brittle White Cast Layer (WCL) containing micro-cracks and tensile residual stresses. This study presents a comprehensive dual-phase Taguchi–GRA–ANFIS optimization framework comparing the performance of non-cryogenic (Phase 1) and deep cryogenically treated (Phase 2, ?196°C for 24 hours) zinc-coated brass electrodes. A Taguchi L9 orthogonal array was utilized to evaluate the impact of Peak Current, Pulse-On Time, Pulse-Off Time, and Wire Tension on Material Removal Rate (MRR) and WCL thickness. Grey Relational Analysis (GRA) identified optimal parameter combinations, revealing that cryogenic treatment in Phase 2 yielded a 73.15% reduction in WCL (from 7.45 ?m to 2.00 ?m) and an improvement in MRR to 20.01 mm³/min at the optimal setting compared to the Phase 1 baseline. To predict these complex nonlinear discharge interactions, an Adaptive Neuro-Fuzzy Inference System (ANFIS) model was developed in MATLAB. The model achieved exceptional predictive accuracy, demonstrating ultra-low Root Mean Square Errors of 1.9587×10?? for Phase 1 and 4.0159×10?? for Phase 2. The findings confirm that cryogenically treated electrodes drastically enhance plasma channel stability, minimizing thermal defects to successfully meet stringent aerospace surface integrity criteria.

Introduction

This study investigates the effect of Deep Cryogenic Treatment (DCT) on zinc-coated brass wire electrodes used in Wire Electrical Discharge Machining (WEDM) of AISI D3 tool steel. The objective is to optimize machining parameters to achieve a high Material Removal Rate (MRR) while minimizing White Cast Layer (WCL) thickness, which is critical for maintaining surface integrity in aerospace applications.

Background

Standard zinc-coated brass wire electrodes suffer from residual stresses and irregular grain structures caused by the wire-drawing process. These defects reduce thermal and electrical conductivity, leading to unstable sparking and faster wire wear. Deep Cryogenic Treatment at −196°C for 24 hours refines the grain structure, removes micro-voids, improves conductivity, enhances plasma stability, and reduces heat transfer to the workpiece.

Key Contributions

The study introduces:

• A dual-phase experimental comparison between untreated and cryogenically treated wire electrodes.
• A combined optimization framework using Taguchi L9 Design of Experiments (DoE), Grey Relational Analysis (GRA), ANOVA, and Adaptive Neuro-Fuzzy Inference System (ANFIS).
• Analysis of the relationship between cryogenic treatment, machining performance, and aerospace surface integrity (AS9100 requirements).
• A microstructure-based explanation linking grain refinement to improved machining performance.

Related Work

Previous studies have independently explored:

• WEDM parameter optimization using Taguchi and Response Surface Methodology.
• Cryogenic treatment to improve electrode performance.
• ANFIS for modeling WEDM processes.

However, very few studies integrate all three approaches into a single framework. This research fills that gap.

Experimental Methodology

Experiments were conducted on a CNC WEDM machine using:

• AISI D3 tool steel as the workpiece.
• 0.25 mm zinc-coated brass wire in untreated (Phase 1) and cryogenically treated (Phase 2) conditions.

A Taguchi L9 orthogonal array optimized four machining parameters:

• Peak Current (15–25 A)
• Pulse-On Time (4–8 μs)
• Pulse-Off Time (15–25 μs)
• Wire Tension (10–14 N)

Each experiment was repeated three times, measuring:

• Material Removal Rate (MRR)
• White Cast Layer (WCL) thickness using SEM.

Optimization and Results

Grey Relational Analysis combined the conflicting objectives of maximizing MRR and minimizing WCL into a single Grey Relational Grade (GRG).

Phase 1 (Non-Cryogenic Wire)

• Optimal parameters: 15 A, 4 μs, 15 μs, 10 N
• GRG: 0.6667
• WCL: 7.45 μm
• MRR: 15.35 mm³/min

Phase 2 (Cryogenically Treated Wire)

• Optimal parameters: 15 A, 4 μs, 25 μs, 14 N
• GRG: 0.8333
• WCL: 2.00 μm (73.15% reduction)
• MRR: 20.01 mm³/min (30.34% improvement)
• Maximum MRR achieved: 72.15 mm³/min

Conclusion

This study successfully implemented a dual-phase Taguchi-GRA-ANFIS framework to optimize the WEDM of AISI D3 tool steel, directly comparing standard and deep cryogenically treated zinc-coated brass electrodes. The following industrial outcomes were achieved: 1) Microstructural enhancement and surface integrity: Deep Cryogenic Treatment (?196°C) induced critical grain refinement within the zinc-coated brass electrode, resulting in a denser, highly ordered crystal lattice. This structural transformation significantly increased the electrode\'s thermal conductivity. Acting as an efficient heat sink, the treated wire stabilized the plasma channel and minimized thermal transfer to the workpiece. Consequently, the melt pool was shallower, reducing the White Cast Layer by 73.15% (down to 2.00 ?m) and successfully satisfying AS9100 aerospace fatigue standards. 2) Productivity enhancement: The optimal GRA setting in Phase 2 yielded a 30.34% improvement in MRR (20.01 mm³/min). At maximum energy settings, the stable cryogenic wire achieved a peak MRR of 72.15 mm³/min while maintaining a WCL of 5.02 ?m. 3) Parameter dominance: ANOVA confirmed Peak Current (Ip) as the governing parameter. Its influence grew from 54.20% (Phase 1) to 62.50% (Phase 2), proving the treated wire\'s superior thermal management under high-energy discharges. 4) Model reliability: The MATLAB ANFIS surrogate model achieved ultra-low RMSE values (4.0159×10?? for Phase 2), providing a highly reliable, transparent tool for virtual process planning and real-time adaptive optimization in smart manufacturing. Future studies will focus on optimizing the cryogenic soaking time and extending this electrode methodology to aerospace superalloys such as Ti-6Al-4V and Inconel 718.

References

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Copyright

Copyright © 2026 Shaik Ummea Salma, S. Somasundaram. 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.