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<p>Medical-grade glass is widely used in lab-on-a-chip and biomedical microfluidic devices because of its optical transparency, chemical inertness, and thermal stability; however, precise micro-hole fabrication remains challenging due to crack formation, lateral overcut, and poor penetration in conventional machining. This study proposes a novel dual-assisted electrochemical discharge machining process combining magnetic field-induced magnetohydrodynamic convection with diamond-grit grinding action for controlled subtractive processing of glass. Compared with conventional ECDM, the proposed GA-MA-ECDM reduced the hole entrance diameter by 11.8%, while improving depth of penetration by 41.9%. Response surface methodology was used to model hole overcut and depth of penetration, with ANOVA confirming model adequacy through F-values of 8.34 and 7.74 and coefficients of determination above 80% and 75%, respectively. Multi-objective optimization using PSO and GA achieved prediction errors of 4.94% for HOC and 0.90% for DOP, demonstrating practical suitability for biomedical glass microdevices.</p> Graphical abstract <p></p>

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Fabrication of holes into glass using ECDM with dual mode assistance: Experimental investigation and process optimization

  • 期刊论文

  • 发表日期：

    2026年8月3日

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  • Arun Nanda,
  • Tarlochan Singh,
  • Sarabjeet Singh Sidhu

摘要

Medical-grade glass is widely used in lab-on-a-chip and biomedical microfluidic devices because of its optical transparency, chemical inertness, and thermal stability; however, precise micro-hole fabrication remains challenging due to crack formation, lateral overcut, and poor penetration in conventional machining. This study proposes a novel dual-assisted electrochemical discharge machining process combining magnetic field-induced magnetohydrodynamic convection with diamond-grit grinding action for controlled subtractive processing of glass. Compared with conventional ECDM, the proposed GA-MA-ECDM reduced the hole entrance diameter by 11.8%, while improving depth of penetration by 41.9%. Response surface methodology was used to model hole overcut and depth of penetration, with ANOVA confirming model adequacy through F-values of 8.34 and 7.74 and coefficients of determination above 80% and 75%, respectively. Multi-objective optimization using PSO and GA achieved prediction errors of 4.94% for HOC and 0.90% for DOP, demonstrating practical suitability for biomedical glass microdevices.

Graphical abstract