OBRABOTKAMETALLOV Vol. 27 No. 2 2025 technology Tool wear rate (TWR, υh) characterizes the rate of electrode material loss during the EDM process [10]. TWR depends on the gap current, electrode material, and dielectric fluid properties. Minimizing TWR is essential for reducing tool costs and increasing the economic efficiency of the process. As a result of rapid solidification of the molten material removed by electrical discharge, a hardened layer known as the “recast layer” of a certain thickness is formed. Controlling the thickness of the recast layer is achieved by optimizing EDM parameters [11]. The area around the machined surface is subjected to thermal effects, forming a heat-affected zone (HAZ). Significant HAZ dimensions can lead to residual stresses and microcracks that affect the mechanical properties of the component. Managing the pulse energy and effectively using the dielectric fluid allows for improved thermal management. The microhardness of the machined surface may change due to thermal effects, which must be considered when evaluating the material characteristics after EDM [12]. Dimensional accuracy and overcut characterize the deviation of the machined part’s dimensions from the specified values. The amount of overcut is influenced by the size of the spark gap, the pulse-on time, and tool wear. Achieving high dimensional accuracy is critical for the production of precision components. Adjusting the EDM process parameters allows for increased productivity, improved surface quality, and extended tool life in accordance with industry standards [13]. The Taguchi method is an effective statistical optimization technique widely used for various technological processes, including EDM. This method allows researchers to plan efficient experiments, optimizing process parameters with a minimal number of experimental runs. The main concept of the Taguchi method relies on orthogonal arrays (OAs) to simultaneously study the influence of several factors on the process output parameters [14]. The L18 OA is often used for EDM optimization, as it provides an effective assessment of the influence of various levels of process parameters. The L18 array allows the analysis of up to eight factors, using two or three different levels of parameters, which is suitable for studying the main EDM parameters, such as pulse-on time, pulse-off time, current, and voltage [15]. Process optimization using the Taguchi method is based on the analysis of the signal-to-noise (S/N) ratio to determine the optimal values of parameters that provide the desired machining results. Three standard S/N ratio criteria are used in EDM studies: “Smaller-the-better” for minimizing SR and TWR, “Largerthe-better” for maximizing MRR, and “Nominal-the-best” for ensuring precision dimensional control. The Taguchi method can improve the efficiency of EDM by identifying optimal machining conditions by minimizing number of experiments and reducing cost and execution time while improving surface integrity and output productivity [16]. In the EDM process, several performance metrics must be considered simultaneously, as it requires achieving extreme MRR along with minimum SR and TWR. For balanced optimization of these competing criteria, the Utility method is often used, which is a popular tool for multi-criteria optimization. The Utility method transforms different output variables into a single combined index, simplifying the decisionmaking process. The application of the Utility method for EDM optimization involves the following steps: normalization of response values (bringing different performance characteristics to a comparable scale), assigning weights to each response based on its relative importance, and calculating a single utility value by multiplying the normalized values by the corresponding weights and summing the results. The optimal combination of process parameters is determined based on the maximum utility value, after which experimental verification is performed. The application of the Utility method allows manufacturers to find optimal parameter settings, providing an effective framework for balanced optimization of EDM performance indicators [17]. As a result of applying the Utility method, optimization of three key performance parameters of the EDM process was achieved, namely, MRR, SR, and TWR. The use of this method made it possible to balance the requirements for production speed and the quality of the machined surface. The integration of weighted normalization methods into the decision-making system improved its accuracy and reliability. The high process efficiency was made possible through the application of the Taguchi method, which provides a systematic study of the influence of EDM parameters with a minimal experimental test runs. The analysis of the S/N ratio allowed identifying critical parameters needed for accurate process optimization.
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