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dc.contributor.authorSaha, Subhadeep
dc.contributor.authorMondal, Arpan Kumar
dc.contributor.authorČep, Robert
dc.contributor.authorJoardar, Hillol
dc.contributor.authorHaldar, Barun
dc.contributor.authorKumar, Ajay
dc.contributor.authorAlsalah, Naser A.
dc.contributor.authorAtaya, Sabbah
dc.date.accessioned2025-02-18T12:16:24Z
dc.date.available2025-02-18T12:16:24Z
dc.date.issued2024
dc.identifier.citationMachines. 2024, vol. 12, issue 5, art. no. 335.cs
dc.identifier.issn2075-1702
dc.identifier.urihttp://hdl.handle.net/10084/155754
dc.description.abstractInconel 718’s exceptional strength and corrosion resistance make it a versatile superalloy widely adopted in diverse industries, attesting to its reliability. Electrochemical machining (ECM) further enhances its suitability for intricate part fabrication, ensuring complex shapes, dimensional accuracy, stress-free results, and minimal thermal damage. Thus, this research endeavors to conduct a novel investigation into the electrochemical machining (ECM) of the superalloy Inconel 718. The study focuses on unraveling the intricate influence of key input process parameters—namely, electrolytic concentration, tool feed rate, and voltage—on critical response variables such as surface roughness (SR), material removal rate (MRR), and radial overcut (RO) in the machining process. The powerful tool, response surface methodology (RSM), is used for understanding and optimizing complex systems by developing mathematical models that describe the relationships between input and response variables. Under a 95% confidence level, analysis of variance (ANOVA) suggests that electrolyte concentration, voltage, and tool feed rate are the most important factors influencing the response characteristics. Moreover, the incorporation of ANN modeling and the MOGA-ANN optimization algorithm introduces a novel and comprehensive approach to determining the optimal machining parameters. It considers multiple objectives simultaneously, considering the trade-offs between them, and provides a set of solutions that achieve the desired balance between MRR, SR, and RO. Confirmation experiments are carried out, and the absolute percentage errors between experimental and optimized values are assessed. The detailed surface topography and elemental mapping were performed using a scanning electron microscope (SEM). The nano/micro particles of Inconel 718 metal powder, obtained from ECM sludge/cakes, along with the released hydrogen byproducts, offer promising opportunities for recycling and various applications. These materials can be effectively utilized in powder metallurgy products, leading to enhanced cost efficiency.cs
dc.language.isoencs
dc.publisherMDPIcs
dc.relation.ispartofseriesMachinescs
dc.relation.urihttps://doi.org/10.3390/machines12050335cs
dc.rights© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectelectrochemical machiningcs
dc.subjectinconel 718cs
dc.subjectmaterial removal ratecs
dc.subjectMOGA-ANNcs
dc.subjectsurface morphologycs
dc.subjectECM by-productscs
dc.titleMulti-response optimization of electrochemical machining parameters for Inconel 718 via RSM and MOGA-ANNcs
dc.typearticlecs
dc.identifier.doi10.3390/machines12050335
dc.rights.accessopenAccesscs
dc.type.versionpublishedVersioncs
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume12cs
dc.description.issue5cs
dc.description.firstpageart. no. 335cs
dc.identifier.wos001232805300001


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Zobrazit minimální záznam

© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
Kromě případů, kde je uvedeno jinak, licence tohoto záznamu je © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.