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Machining of shape-memory alloys using electrical discharge machining with an elaborate study of optimization approaches: a review

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Abstract

Shape-memory alloys (SMAs) are preferred currently for multifarious purposes because of their exceptional properties as compared to counterparts, viz. shape-memory effect, superelasticity, corrosion resistance, bioadaptability, resistance to wear, etc. A multitude of research activities regarding the machining of SMAs has been done. The conventional machining techniques have shortcomings related to surface morphology as it generates undesirable tool wear and low accuracy of machined parts. Among the unconventional methods, electrical discharge machining (EDM) and its allied variations have created a buzz in machining of SMAs. This study is an effort to carry out an investigation of the work done by vivid researchers in machining of SMAs using die-sinking EDM and die-sinking micro-EDM. The input parameters and response features of EDM are discussed. The research focusing on nickel titanium (NiTi)-based, copper (Cu)-based and other SMAs using EDM in particular is elaborated here. The general overview of several optimization methods, viz. non-traditional methods, multi-criteria decision making methods, and statistical methods, is presented elaborately. A review of optimization with their implementation in EDM machining of SMAs by researchers is incorporated in this article. The techniques for advanced processing of SMAs and hybrid EDM methods are reviewed. The future scope of research on the current topic is suggested through this review.

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Authors and Affiliations

  1. Department of Mechanical Engineering, National Institute of Technology Nagaland, Nagaland, 797103, India

    Subhankur Dutta, Amit Kumar Singh & Bappi Paul

  2. Department of Mechanical Engineering, National Institute of Technology Jamshedpur, Jamshedpur, Jharkhand, India

    Mani Kant Paswan

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Dutta, S., Singh, A.K., Paul, B. et al. Machining of shape-memory alloys using electrical discharge machining with an elaborate study of optimization approaches: a review. J Braz. Soc. Mech. Sci. Eng. 44, 557 (2022). https://doi.org/10.1007/s40430-022-03826-y

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