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<p>This study explores the potential of incorporating titanium diboride (TiB<sub>2</sub>) and cow dung ash (CDA) in various weight proportions (0:0, 7.5:2.5, 5:5, 2.5:7.5) into the Al6061 alloy base matrix. Performance evaluation includes density, hardness, tensile and impact strength, porosity, wear mechanisms, and corrosion resistance of resulting green hybrid aluminum matrix composites (g-HAMC). Obtained results unequivocally indicate that no single green hybrid composite alternative excels in all attributes simultaneously. Consequently, considering all attributes, a two-stage technique (CRITIC-MABAC) is adopted to identify the optimal alternative. The CRITIC approach is utilized to determine attribute weights, and the MABAC approach is for ranking g-HAMC alternatives. This hybrid method reveals that alternative G3 (2.5:7.5; CDA: TiB<sub>2</sub>) exhibited optimum characteristics, and this MCMD approach was noted to be efficient for optimal alternative selection with various decision parameters.</p>

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A Hybrid CRITIC-MABAC Approach to Select the Optimal Alternative of TiB2 and Natural Reinforcement (CDA) Filled Al6061 Hybrid Composite

  • 期刊论文

  • 发表日期：

    2025年1月2日

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  • Vishista Kaushik,
  • Amit Aherwar

摘要

This study explores the potential of incorporating titanium diboride (TiB2) and cow dung ash (CDA) in various weight proportions (0:0, 7.5:2.5, 5:5, 2.5:7.5) into the Al6061 alloy base matrix. Performance evaluation includes density, hardness, tensile and impact strength, porosity, wear mechanisms, and corrosion resistance of resulting green hybrid aluminum matrix composites (g-HAMC). Obtained results unequivocally indicate that no single green hybrid composite alternative excels in all attributes simultaneously. Consequently, considering all attributes, a two-stage technique (CRITIC-MABAC) is adopted to identify the optimal alternative. The CRITIC approach is utilized to determine attribute weights, and the MABAC approach is for ranking g-HAMC alternatives. This hybrid method reveals that alternative G3 (2.5:7.5; CDA: TiB2) exhibited optimum characteristics, and this MCMD approach was noted to be efficient for optimal alternative selection with various decision parameters.