https://doi.org/10.1140/epjp/s13360-026-07693-7
Regular Article
Multi-response surface characterization and process optimization in wire EDM of NiTi shape memory alloys
1
Department of Mechanical Engineering, Faculty of Engineering, Architecture and Design, Bartın University, Bartın, Turkey
2
Department of Manufacturing Engineering, Faculty of Technology, Gazi University, Ankara, Turkey
3
Department of Mechanical Engineering, Faculty of Engineering, Cankiri Karatekin University, 18100, Çankırı, Turkey
4
Industrial Tribology Laboratory, Department of Mechanical Engineering, M. E. S. Wadia College of Engineering, S. P. Pune University, 411001, Pune, India
5
Department of Metallurgy and Materials Engineering, Technology Faculty, Pamukkale University, Kınıklı Campus, Denizli, Turkey
a
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b
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Received:
3
March
2026
Accepted:
14
April
2026
Published online:
29
April
2026
Abstract
Advanced materials produced through cutting-edge technologies play a crucial role in fulfilling the evolving demands of both consumers and industry. Consequently, material scientists actively engage in research focused on the production and enhancement of these materials’ properties. Among these, nickel–titanium (NiTi) shape memory alloys stand out due to their exceptional characteristics, including high elastic deformation capability, superior strength, and excellent corrosion resistance. However, these same properties also render NiTi alloys difficult to machine using conventional techniques, often leading to significant tool wear and suboptimal surface quality. To address these challenges, wire electrical discharge machining (WEDM) has emerged as a more effective alternative to traditional machining methods for processing NiTi alloys. The primary objective of this study is to minimize material deformation by achieving the lowest possible surface roughness during the WEDM of NiTi shape memory alloys. These alloys are commonly utilized in high-performance sectors such as aerospace and defense, where precision and surface integrity are critical. Another goal is to optimize the machining parameters to enable accurate cutting without necessitating any additional finishing operations. In this study, gray relational analysis (GRA), a prominent multi-criteria decision-making method, was employed to optimize the WEDM process parameters. An experimental design based on the Taguchi L27 (35) orthogonal array was used to systematically investigate the effects of machining parameters. Analysis of variance (ANOVA) was then conducted to quantify the influence of each parameter. The findings indicate that the most significant control factors are: current for kerf width (73.67%), dielectric fluid flow rate for burr height (37.26%), servo voltage for machining time (59.24%), and current for surface roughness (61.16%). Furthermore, two-way interactions between control factors were also found to have a notable impact on machining outcomes. The optimization results were validated through confirmatory experiments, and the high correlation coefficients obtained support the reliability of the developed mathematical models.
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© The Author(s), under exclusive licence to Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2026
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
