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<p>CFRP composite sheets are valued for their outstanding properties, with micro-perforations finding diverse applications. This study introduces an electrothermal model to predict hole quality, measured as roundness error, considering the effects of capacitance and voltage through a thermal profile. Roundness error is assessed using iso-contour lines of the melting temperature at epoxy and fiber layers. The model is simulated under nine conditions, varying voltage and capacitance levels, to predict roundness error trends. Results demonstrate an initial increase in roundness error with capacitance from 10 nF to 100 nF, followed by a decrease up to 400 nF at constant voltage. A 15-micron average difference in roundness error between layers is observed. Experimental and simulated roundness error comparisons at the epoxy layer’s surface reveal a marginal 9 % difference, validating the numerical model’s accuracy and reliability for predictive analysis and machining optimization.</p>

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Electrothermal modeling of μ-EDM drilling for prediction of hole quality in CFRP laminates

  • 期刊论文

  • 发表日期：

    2025年5月5日

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  • Nitish Kaushik,
  • Sanjay Kumar Jha,
  • Ravi Shankar Anand

摘要

CFRP composite sheets are valued for their outstanding properties, with micro-perforations finding diverse applications. This study introduces an electrothermal model to predict hole quality, measured as roundness error, considering the effects of capacitance and voltage through a thermal profile. Roundness error is assessed using iso-contour lines of the melting temperature at epoxy and fiber layers. The model is simulated under nine conditions, varying voltage and capacitance levels, to predict roundness error trends. Results demonstrate an initial increase in roundness error with capacitance from 10 nF to 100 nF, followed by a decrease up to 400 nF at constant voltage. A 15-micron average difference in roundness error between layers is observed. Experimental and simulated roundness error comparisons at the epoxy layer’s surface reveal a marginal 9 % difference, validating the numerical model’s accuracy and reliability for predictive analysis and machining optimization.