Multi-Objective Optimization of Magnetic-Assisted Titanium Electropolishing in a Deep Eutectic Solvent Using Taguchi-TOPSIS Methodology
Titanium and its alloys present machining challenges that necessitate post-machining surface finishing to guarantee functional reliability and surface integrity. Because traditional methods often rely on hazardous acidic media, recent sustainable manufacturing advances prioritize eco-friendly Deep Eutectic Solvents (DESs); however, achieving a balance between maximizing Material Removal Rate (MRR) and minimizing Surface Roughness remains a complex multi-variable optimization challenge. This study investigates the magnetic-assisted green electropolishing of titanium using a propylene glycol and choline chloride DES. A Taguchi L9 orthogonal array, Two-Way Analysis of Variance (ANOVA), and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) were synergistically employed to evaluate the systemic interactions between applied voltage (6 V, 8 V, 10 V) and Agitation Modality (static, mechanical stirring, 0.5 T magnetic field). Two-Way ANOVA identified applied voltage as the statistically dominant parameter governing MRR (69.20% contribution), while demonstrating that surface roughness is significantly influenced by parameter interactions. Although TOPSIS mathematically balanced the competing numerical metrics, morphological SEM analysis confirmed that the synergistic combination of 8 V and a 0.5 T magnetic field achieved the optimal functional condition, yielding a featureless, defect-free 3D surface topography (Ra = 0.1610 µm). Ultimately, incorporating external magnetic field assistance effectively overcomes the mass-transport limitations of viscous DES media through controlled magnetohydrodynamic (MHD) convection, providing a robust methodology to balance high material removal efficiency with ultra-smooth surface integrity.
Authors
- Kartika Nur Anisa (ORCID: https://orcid.org/0000-0002-0776-1721)
- Muslim Mahardika (ORCID: https://orcid.org/0000-0003-4704-3924)
- Rizky Astari Rahmania (ORCID: https://orcid.org/0009-0001-5692-9332)
- Gunawan Setia Prihandana (ORCID: https://orcid.org/0000-0003-3709-2036)
- Nor Hasrul Akhmal Ngadiman (ORCID: https://orcid.org/0000-0002-1128-6556)
- Chandrawati Putri Wulandari (ORCID: https://orcid.org/0000-0002-0115-9115)
- Asseghaf Bintang Ramadhani (ORCID: https://orcid.org/0009-0007-8980-779X)
- Muhammad Fawwaz Kanziwa
- Eurison Jeyandra Tanamal
Institutions
- Universitas Gadjah Mada (ID)
- Airlangga University (ID)
- University of Technology Malaysia (MY)
Publication Details
- Journal
- Applied System Innovation
- Published
- 2026-09-29
- DOI
- https://doi.org/10.3390/asi9100206
- Primary Topic
- Advanced Machining and Optimization Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00