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<p>Mesoscale surface integrity is extremely important in automotive and aerospace industry applications that must satisfy strict requirements on surface roughness (Ra) and microhardness (MH). Inconel 718 (IN718), a nickel-based super-alloy, is widely used in the aforementioned areas. Since conventional machining of IN718 is complicated by the material’s fast strain hardening, other methods like electric discharge machining (EDM) should be selected for this purpose. However, EDM may suffer from low erosion rate and poor surface finish. To overcome these limitations, the present study analyzed a powder-mixed EDM set up employing cryogenically treated (CT) copper (Cu) electrodes and nano-sillimanite waste fluid (NSWF, obtained by adding nano-sillimanite powder to waste cooking oil). Performance index measures (PIMs) such as Ra, MH, recast layer thickness (RLT), and energy efficiency (EE) were compared for both the non-treated (NT) and CT Cu electrodes. The new EDM set up was also compared with another EDM set up using nano-sillimanite kerosene oil (NSKO) to evaluate its environmental sustainability. PIMs were analyzed with respect to EDM processing parameters such as spark voltage (V<sub>S</sub>), peak current (I<sub>P</sub>), sillimanite powder concentration (C<sub>P</sub>), and surfactant concentration (S<sub>C</sub>), also considering binary combinations of EDM parameters (V<sub>S</sub>, I<sub>P</sub>), (V<sub>S</sub>, C<sub>P</sub>) and (V<sub>S</sub>, S<sub>C</sub>). An Artificial neural network (ANN) modelling, desirability analysis and multi-objective optimization were utilized (i) to assess the level of correlation between forecasted and experimentally recorded PIMs values, and (ii) to find the best combination of EDM process parameters optimizing EDM performance. The EDM set up with the CT Cu electrode outperformed the EDM set up with the NT Cu electrode achieving better surface finish, higher microhardness, less recasting, and better energy efficiency: in particular, 30.32% lower Ra, 21.40% better MH, 25.02% reduction in RLT, and 18.99% increment in EE setting EDM process parameters at their upper bounds. Moreover, the EDM-NSWF set up could reduce CO<sub>2</sub> emissions by 97.27 ± 0.889% with respect to standard EDM using kerosene dielectric fluid vs. only 3.38 ± 4.33% reduction achieved by EDM-NSKO.</p>

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Mesoscale investigation on powder-mixed dielectric EDM of Inconel 718 combining nano-Sillimanite waste fluid and cryogenically treated Cu electrodes: Machine learning modelling and experimental analysis

  • 期刊论文

  • 发表日期：

    2026年2月21日

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  • Muhammad Sana,
  • Muhammad Asad Ali,
  • Sana Ehsan,
  • Aqil Inam,
  • Catalin Iulian Pruncu,
  • Luciano Lamberti

摘要

Mesoscale surface integrity is extremely important in automotive and aerospace industry applications that must satisfy strict requirements on surface roughness (Ra) and microhardness (MH). Inconel 718 (IN718), a nickel-based super-alloy, is widely used in the aforementioned areas. Since conventional machining of IN718 is complicated by the material’s fast strain hardening, other methods like electric discharge machining (EDM) should be selected for this purpose. However, EDM may suffer from low erosion rate and poor surface finish. To overcome these limitations, the present study analyzed a powder-mixed EDM set up employing cryogenically treated (CT) copper (Cu) electrodes and nano-sillimanite waste fluid (NSWF, obtained by adding nano-sillimanite powder to waste cooking oil). Performance index measures (PIMs) such as Ra, MH, recast layer thickness (RLT), and energy efficiency (EE) were compared for both the non-treated (NT) and CT Cu electrodes. The new EDM set up was also compared with another EDM set up using nano-sillimanite kerosene oil (NSKO) to evaluate its environmental sustainability. PIMs were analyzed with respect to EDM processing parameters such as spark voltage (VS), peak current (IP), sillimanite powder concentration (CP), and surfactant concentration (SC), also considering binary combinations of EDM parameters (VS, IP), (VS, CP) and (VS, SC). An Artificial neural network (ANN) modelling, desirability analysis and multi-objective optimization were utilized (i) to assess the level of correlation between forecasted and experimentally recorded PIMs values, and (ii) to find the best combination of EDM process parameters optimizing EDM performance. The EDM set up with the CT Cu electrode outperformed the EDM set up with the NT Cu electrode achieving better surface finish, higher microhardness, less recasting, and better energy efficiency: in particular, 30.32% lower Ra, 21.40% better MH, 25.02% reduction in RLT, and 18.99% increment in EE setting EDM process parameters at their upper bounds. Moreover, the EDM-NSWF set up could reduce CO2 emissions by 97.27 ± 0.889% with respect to standard EDM using kerosene dielectric fluid vs. only 3.38 ± 4.33% reduction achieved by EDM-NSKO.