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  • 标题:Intelligent Machining of Shape Memory Alloys
  • 本地全文:下载
  • 作者:Kapil Gupta ; Kapil Gupta
  • 期刊名称:Advances in Science and Technology Research Journal
  • 印刷版ISSN:2080-4075
  • 电子版ISSN:2299-8624
  • 出版年度:2021
  • 卷号:15
  • 期号:3
  • 页码:43-53
  • DOI:10.12913/22998624/138303
  • 语种:English
  • 出版社:Society of Polish Mechanical Engineers and Technicians
  • 摘要:Shape memory alloys are important biomaterials but difficult-to-machine (DTM). Their machining needs to be done using intelligent techniques to obtain a better machinability. Hybrid optimization is one of such techniques which can perform modeling and optimization of machining parameters for the best values of machinability indicators. Wire electric discharge machining (WEDM) of shape memory alloy has been found as a prominent alternate to the conventional machining techniques; however it needs the assistance of intelligent techniques to machine such materials to obtain the optimum values of machinability indicators. In this paper, WEDM of shape memory alloy Ni55.8Ti was reported. WEDM was carried out by varying four process parameters i.e. servo voltage SV, pulse-on time Pon, pulse-off time Poff, and wire feed rate WF using Taguchi L16 robust design of experiment technique. A hybrid optimization technique TOPSIS-Fuzzy-PSO has been successfully used to optimize these parameters (SV-50V; Pon-1µs; Poff-17 µs; WF-4 m/min) for the best possible values of material removal rate (MRR) – 0.049 g/min, maximum roughness – 11.45 µm, and recast layer – 22.10 µm simultaneously.
  • 关键词:optimization;shape memory alloy;TOPSIS-Fuzzy;WEDM
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