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<p>The growing demand for lightweight, high-strength materials in automotive and aerospace industries has positioned aluminum-based hybrid metal matrix composites (HMMCs) as game-changing alternatives to conventional alloys. However, their enhanced mechanical properties present significant machinability challenges that require advanced processing strategies. This study addresses this critical gap by systematically investigating the electrical discharge machining (EDM) characteristics of a novel Al6063‐10SiC‐5B4C‐Mg hybrid composite fabricated through pressurized stir casting. Employing Response Surface Methodology with Central Composite Rotatable Design (CCRD), we developed robust second-order predictive models for three critical performance indicators: material removal rate (MRR), electrode wear rate (EWR), and surface roughness (SR). Comprehensive statistical validation through ANOVA and residual diagnostics confirmed excellent model adequacy at a 95% confidence level, with determination coefficients exceeding 0.95 for all responses. Our systematic parametric analysis revealed that current, pulse-on time, and spark gap constitute the dominant factors governing machining performance, with their interactive and quadratic effects playing crucial roles in process behavior. Through multi-objective optimization, we identified an optimal parameter combination (current: 7A, pulse-on time: 56&#xa0;µs, spark gap: 7&#xa0;mm, pulse-off time: 9&#xa0;µs, voltage: 41&#xa0;V) that simultaneously achieves maximum productivity (MRR: 17.8304&#xa0;mm<sup>3</sup>/min), controlled tool consumption (EWR: 0.2662&#xa0;mm<sup>3</sup>/min), and superior surface quality (SR: 7.619&#xa0;µm). Scanning electron microscopy of the optimized machined surfaces revealed excellent surface integrity, characterized by minimal crater formation, negligible microcracking, and a significantly reduced heat-affected zone—key quality requirements for aerospace-grade components. The validated predictive models exhibited exceptional accuracy with prediction errors ranging from 2.99 to 4.85%, establishing their practical utility for industrial implementation. This study uniquely presents a material-specific, experimentally validated predictive framework for EDM of pressurized stir-cast Al6063-based hybrid composites, offering practical guidelines to balance productivity, tool life, and surface quality for demanding aerospace and automotive applications.</p>

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Multi-response Optimization of EDM Parameters for Aerospace-Grade Al6063‐SiC‐B4C Hybrid Metal Matrix Composites Using Response Surface Methodology

  • 期刊论文

  • 发表日期：

    2026年4月24日

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  • Gurpreet Singh Matharou,
  • Aparna Sharma,
  • Kamaljit Singh,
  • Varun Singhal,
  • Bhaskar Chandra Kandpal,
  • Simran Kaur,
  • Daksh Shelly

摘要

The growing demand for lightweight, high-strength materials in automotive and aerospace industries has positioned aluminum-based hybrid metal matrix composites (HMMCs) as game-changing alternatives to conventional alloys. However, their enhanced mechanical properties present significant machinability challenges that require advanced processing strategies. This study addresses this critical gap by systematically investigating the electrical discharge machining (EDM) characteristics of a novel Al6063‐10SiC‐5B4C‐Mg hybrid composite fabricated through pressurized stir casting. Employing Response Surface Methodology with Central Composite Rotatable Design (CCRD), we developed robust second-order predictive models for three critical performance indicators: material removal rate (MRR), electrode wear rate (EWR), and surface roughness (SR). Comprehensive statistical validation through ANOVA and residual diagnostics confirmed excellent model adequacy at a 95% confidence level, with determination coefficients exceeding 0.95 for all responses. Our systematic parametric analysis revealed that current, pulse-on time, and spark gap constitute the dominant factors governing machining performance, with their interactive and quadratic effects playing crucial roles in process behavior. Through multi-objective optimization, we identified an optimal parameter combination (current: 7A, pulse-on time: 56 µs, spark gap: 7 mm, pulse-off time: 9 µs, voltage: 41 V) that simultaneously achieves maximum productivity (MRR: 17.8304 mm3/min), controlled tool consumption (EWR: 0.2662 mm3/min), and superior surface quality (SR: 7.619 µm). Scanning electron microscopy of the optimized machined surfaces revealed excellent surface integrity, characterized by minimal crater formation, negligible microcracking, and a significantly reduced heat-affected zone—key quality requirements for aerospace-grade components. The validated predictive models exhibited exceptional accuracy with prediction errors ranging from 2.99 to 4.85%, establishing their practical utility for industrial implementation. This study uniquely presents a material-specific, experimentally validated predictive framework for EDM of pressurized stir-cast Al6063-based hybrid composites, offering practical guidelines to balance productivity, tool life, and surface quality for demanding aerospace and automotive applications.