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<p>This correlative investigation presents a comparative performance analysis on machining characteristics by wire-cut electrical discharge machining (WEDM) outcomes when processing a titanium matrix composite (TMC) under diversifying input parameters. Experimental investigation focuses on metrics such as material removal rate (MRR), surface roughness (SR), kerf width (KW), and overcut (OC). An innovative multi-objective optimization (MOO) algorithm like desirable ant colony optimization (DACO) is proposed here, which is correlated with desirable particle swarm optimization (DPSO). DACO achieved a combined desirability score of 0.804, which rose to 0.813 with the implementation of DPSO. Comparing these two algorithms, DPSO outperformed DACO by approximately 1.119% in terms of desirability, showcasing its superior optimization capabilities. Optimal performance measures values are 3.847&#xa0;mm³/min for MRR, 0.796&#xa0;μm for SR, 0.354&#xa0;mm for KW, and 0.105&#xa0;mm for OC.</p>

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A Correlative Approach on Machining Characteristics by WEDM Using an Innovative Desirable Ant Colony Optimization Algorithm

  • 期刊论文

  • 发表日期：

    2026年3月30日

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  • Soutrik Bose,
  • Neladri Bose,
  • Munna Chowdhury

摘要

This correlative investigation presents a comparative performance analysis on machining characteristics by wire-cut electrical discharge machining (WEDM) outcomes when processing a titanium matrix composite (TMC) under diversifying input parameters. Experimental investigation focuses on metrics such as material removal rate (MRR), surface roughness (SR), kerf width (KW), and overcut (OC). An innovative multi-objective optimization (MOO) algorithm like desirable ant colony optimization (DACO) is proposed here, which is correlated with desirable particle swarm optimization (DPSO). DACO achieved a combined desirability score of 0.804, which rose to 0.813 with the implementation of DPSO. Comparing these two algorithms, DPSO outperformed DACO by approximately 1.119% in terms of desirability, showcasing its superior optimization capabilities. Optimal performance measures values are 3.847 mm³/min for MRR, 0.796 μm for SR, 0.354 mm for KW, and 0.105 mm for OC.