Abstract
Manufacturing companies employ advanced machining techniques to create complex and accurate products, which require selecting optimum process parameters to achieve the desired quality and cost-effectiveness. Traditional techniques such as Design of Experiments and Response Surface Methodology optimize locally and may not be sufficient for complex systems. This study aims to optimize the Wire Electrical Discharge Machining process of AISI D3 material using Response Surface Methodology and Teaching and Learning-Based Optimization (TLBO), which can optimize globally. The proposed model can improve the quality and cost-effectiveness of the machining process, making it more suitable for various manufacturing applications.
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