OBRABOTKAMETALLOV technology Vol. 27 No. 2 2025 In addition, it was established that the electrical conductivity of the workpiece material, along with current and voltage measurements in the discharge, has a significant impact on machining performance and, in particular, on surface smoothness [18]. Adetailed study of the machining methods of shape memory alloys (SMAs) was carried out, in which the effectiveness of EDM and its variations, including conventional die-sinking EDM and die-sinking microEDM, were evaluated. SMAs, possessing unique properties such as the shape memory effect, superelasticity, high corrosion resistance, and biocompatibility, particularly NiTi-based alloys and copper-based alloys, are widely in demand in various applications. EDM is a promising alternative to conventional machining methods, as it can solve problems related to tool wear, ensure high machining accuracy, and enables lowaccuracy CNC machining. The present study focuses on analyzing the influence of EDM input parameters on response behavior when machining SMAs, with an emphasis on NiTi alloy systems. The review examines various optimization strategies for EDM parameters, focusing on non-conventional approaches in addition to widely used statistical methods and multi-criteria decision-making methods. Particular attention is paid to both hybrid EDM methods and advanced technological approaches used in the processing of shape memory alloys [19]. An extensive review is devoted to the machining of shape memory alloys by EDM, with an emphasis on methods for processing NiTi-based SMAs. The wide industrial implementation of SMAs as industrial materials is emphasized due to their remarkable properties, finding applications in orthopedic implants, actuators, aerospace components, and biomedical devices. It is noted that efficient machining of NiTi SMAs remains a complex challenge. This review analyzes experimental, theoretical as well as modeling and optimization-based approaches used to describe EDM, WEDM, and conventional machining processes for SMAs. It is emphasized that improving machining efficiency requires optimal selection of process parameters, suitable electrode tools, and dielectric fluids. Among EDM methods, WEDM is the most extensively studied in the context of SMA cutting, outpacing die-sinking EDM and powder-mixed EDM used to enhance SMA processing performance and accuracy [20]. Several studies have investigated the optimization of WEDM process parameters for Nitinol shape memory alloys (nitinol – nickel-titaniumalloy), which exhibit the ability to return to their original shape under the influence of thermal or mechanical factors. In [21], desirability function analysis (DFA) combined with the analytic hierarchy process (AHP) is used within a multi-criteria decision making (MCDM) framework to determine optimal machining conditions. The influence of four WEDM input parameters, namely, pulseon time, pulse-off time, wire tension, and wire feed, on kerf width, MRR, and SR was investigated. Based on DFA-AHP methods, the optimal machining parameters were determined to be: pulse-on time 120 μs, pulse-off time 55 μs, wire tension 8 kgf, and wire feed 3 m/min. The results were confirmed by S/N ratio analysis using the Taguchi method. The combination of results showed that the MCDM approach successfully identifies effective process parameters to enhance the performance during the WEDM processing of Nitinol [21]. In [22], the WEDM of superelastic nickel-titanium SMA (Ni54.1Ti), driven by the difficulties of traditional machining methods investigated is studied. NiTi-based alloys require precision machining methods, especially in critical applications such as the medical industry. The assessment focused on the impact of pulse-on time, pulse-off time, and gap current on two key output metrics: MRR and SR. Experiments that systematically assessed these parameters were designed using a Taguchi L27 mixed orthogonal array (L27 OA) and demonstrated that pulse-on time is a key parameter influencing the MRR and SR values [22]. The optimization of surface roughness of NiTi SMA in EDM using the Taguchi method was investigated in [23]. NiTi-based alloys are widely used as “smart” materials in various industries, including the security industry, the maritime sector, and the aerospace field, due to their unique properties. Due to the high hardness of this material, processing with conventional tools presents significant difficulties, making EDM a suitable solution. The machining quality of NiTi largely depends on surface roughness parameters. EDM process variables were optimized using a systematic Taguchi method to improve performance. The research results demonstrate the possibility of improving the surface quality of NiTi-based alloys and, therefore, confirm the effectiveness of EDM as a precision machining method for this challenging material [23].
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