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A study on the μwire-EDM of Ni55.8Ti shape memory superalloy: an experimental investigation and a hybrid ANN/PSO approach for optimization

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dc.contributor.author Akar, Samet
dc.contributor.author Seyedzavvar, Mirsadegh
dc.contributor.author Boğa, Cem
dc.date.accessioned 2023-11-23T11:31:40Z
dc.date.available 2023-11-23T11:31:40Z
dc.date.issued 2023-03
dc.identifier.citation Akar, Samet; Seyedzavvar, Mirsadegh; Boğa, Cem. (2023)." A study on the μwire-EDM of Ni55.8Ti shape memory superalloy: an experimental investigation and a hybrid ANN/PSO approach for optimization", Journal Of The Brazilian Society Of Mechanical Sciences And Engineering, Vol.45, No.3. tr_TR
dc.identifier.issn 1678-5878
dc.identifier.uri http://hdl.handle.net/20.500.12416/6606
dc.description.abstract The unique properties of high hardness, toughness, strain hardening, and development of strain-induced martensite of nickel-titanium superalloys made the micro-wire electro discharge machining (mu wire-EDM) process one of the main practical options to cut such alloys in micro-scale. This paper presents the results of a comprehensive study to address the response variables of Ni55.8Ti superalloy in mu wire-EDM process, including the kerf width (KW), material removal rate (MRR), arithmetic mean surface roughness (R-a) and white layer thickness (WLT). To this aim, the effects of pulse on-time (T-on), pulse off-time (T-off), discharge current (I-d) and servo voltage (SV) as input parameters were investigated using the experiments conducted based on Taguchi L-27 orthogonal array. The results were employed in the analysis of variance (ANOVA) to examine the significance of input parameters and their interactions with the output variables. An optimization approach was adopted based on a hybrid neural network/particle swarm optimization (ANN/PSO) technique. The ANN was employed to achieve the models representing the correlation between the input parameters and output variables of the mu wire-EDM process. The weight and bias factor matrices were obtained by ANN in MATLAB and together with the feed forward/backpropagation model and developed functions based on PSO methodology were used to optimize the input parameters to achieve the minimum quantities of KW, R-a and WLT and the maximum value of MRR, individually and in an accumulative approach. The results represented a maximum accumulative error of nearly 8% that indicated the precision of the developed model and the reliability of the optimization approach. At the optimized level of input parameters obtained through the accumulative optimization approach, the KW, R-a, and WLT remained nearly intact as compared with the levels of responses obtained in the individual optimization approach, while there was a sacrifice in the machining efficiency and reduction in the MRR in the mu wire-EDM process of Nitinol superalloy. tr_TR
dc.language.iso eng tr_TR
dc.relation.isversionof 10.1007/s40430-023-04100-5 tr_TR
dc.rights info:eu-repo/semantics/closedAccess tr_TR
dc.subject Ni55.8Ti Superalloy tr_TR
dc.subject µwire-EDM tr_TR
dc.subject ANN/PSO tr_TR
dc.subject Kerf Width tr_TR
dc.subject Material Removal Rate tr_TR
dc.subject Surface Roughness tr_TR
dc.subject White Layer Thickness tr_TR
dc.title A study on the μwire-EDM of Ni55.8Ti shape memory superalloy: an experimental investigation and a hybrid ANN/PSO approach for optimization tr_TR
dc.type article tr_TR
dc.relation.journal Journal Of The Brazilian Society Of Mechanical Sciences And Engineering tr_TR
dc.contributor.authorID 315516 tr_TR
dc.identifier.volume 45 tr_TR
dc.identifier.issue 3 tr_TR
dc.contributor.department Çankaya Üniversitesi, Mühendislik Fakültesi, Makine Mühendisliği Bölümü tr_TR


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