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<p>Titanium alloys unique properties are essential across a wide range of industries such as aerospace, biomedical and automobile. However, high strength and low thermal conductivity of these materials make them as difficult-to-cut materials. Machining of titanium alloys with conventional machining methods has been faced so many challenges like poor surface finish and high tool wear. So, non-conventional machining methods are employed for machining of titanium alloys. In the present work, electric discharge machining (EDM) is used for machining of Ti-6Al-7Nb work material. Experiments are conducted by selecting Taguchi OA which contains four-factor, four-level fractional factorial design with parameters of current, pulse on-time, voltage and powder concentration. Morphological features such as material removal rate (MRR), electrode wear rate (TWR) and topographical characteristics like surface roughness (SR), surface crack density (SCD) and white layer thickness (WLT) are studied. To achieve superior process performance, an optimal combination of parameters is determined. This is accomplished by applying utility theory, which integrates multiple performance indicators into a unified metric known as the overall utility degree. The parameter combination that yields the highest overall utility is considered the most effective. In addition, predicted mathematical models of EDMed responses are generated using artificial neuro-fuzzy inference system (ANFIS) using MATLAB 21. The performance of the ANFIS model is assessed by comparing it with the predicted outcomes of the Taguchi model. It is noticed that ANFIS model consistently outperformed the Taguchi model.</p>

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Modeling and Optimization of EDM Process Parameters for Ti-6Al-7Nb Using ANFIS and Utility Theory

  • 期刊论文

  • 发表日期：

    2026年3月6日

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  • Thrinadh Jadam,
  • Anurag Jasti,
  • Srikar Potnuru

摘要

Titanium alloys unique properties are essential across a wide range of industries such as aerospace, biomedical and automobile. However, high strength and low thermal conductivity of these materials make them as difficult-to-cut materials. Machining of titanium alloys with conventional machining methods has been faced so many challenges like poor surface finish and high tool wear. So, non-conventional machining methods are employed for machining of titanium alloys. In the present work, electric discharge machining (EDM) is used for machining of Ti-6Al-7Nb work material. Experiments are conducted by selecting Taguchi OA which contains four-factor, four-level fractional factorial design with parameters of current, pulse on-time, voltage and powder concentration. Morphological features such as material removal rate (MRR), electrode wear rate (TWR) and topographical characteristics like surface roughness (SR), surface crack density (SCD) and white layer thickness (WLT) are studied. To achieve superior process performance, an optimal combination of parameters is determined. This is accomplished by applying utility theory, which integrates multiple performance indicators into a unified metric known as the overall utility degree. The parameter combination that yields the highest overall utility is considered the most effective. In addition, predicted mathematical models of EDMed responses are generated using artificial neuro-fuzzy inference system (ANFIS) using MATLAB 21. The performance of the ANFIS model is assessed by comparing it with the predicted outcomes of the Taguchi model. It is noticed that ANFIS model consistently outperformed the Taguchi model.