Zobrazit minimální záznam

dc.contributor.authorShanmugasundar, G.
dc.contributor.authorMahanta, Tapan K.
dc.contributor.authorČep, Robert
dc.contributor.authorKalita, Kanak
dc.date.accessioned2023-02-16T13:52:02Z
dc.date.available2023-02-16T13:52:02Z
dc.date.issued2022
dc.identifier.citationProcesses. 2022, vol. 10, issue 12, art. no. 2645.cs
dc.identifier.issn2227-9717
dc.identifier.urihttp://hdl.handle.net/10084/149117
dc.description.abstractDue to the increase in the impact of different manufacturing processes on the environment, green manufacturing processes are the prime focus of many current pieces of research. In the current article, a green machining process for stainless steel and SS304 and AISI1045 steel has been optimized using newly developed Fuzzy Measurement Alternatives and Ranking according to the COmpromise Solution (F-MARCOS) method in the form of two case studies. In the first case study, nose radius, cutting speed, depth of cut, and feed rate are selected as the process parameters whereas surface roughness, consumption of electrical energy, and power factor are the outputs. In the second case study width of cut, depth of cut, feed rate, and cutting speed were the process parameters and material removal rate (MRR), active energy consumption (ACE), and surface roughness (Ra) are the response variables. The MARCOS method ranks the alternatives based on the ideal and anti-ideal solutions for the different criteria. The inclusion of fuzzy logic adds worth to the model by using a linguistic scale to make the method more practical and flexible. Based on the detailed analysis, it ranked the best alternative in case study one which results in a power factor of 0.862, 26.68 kJ of electrical energy consumption, and surface roughness of 0.36 mu m. In the second case study, the best alternative selected by this method gave an MRR of 2400 mm3/min and Ra of 2.29 mu m and utilizes 53.988 kJ ACE.cs
dc.language.isoencs
dc.publisherMDPIcs
dc.relation.ispartofseriesProcessescs
dc.relation.urihttps://doi.org/10.3390/pr10122645cs
dc.rights© 2022 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.subjectprocess optimizationcs
dc.subjectMCDMcs
dc.subjectfuzzycs
dc.subjectdecision makingcs
dc.subjectmachiningcs
dc.titleNovel fuzzy measurement alternatives and ranking according to the compromise solution-based green machining optimizationcs
dc.typearticlecs
dc.identifier.doi10.3390/pr10122645
dc.rights.accessopenAccesscs
dc.type.versionpublishedVersioncs
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume10cs
dc.description.issue12cs
dc.description.firstpageart. no. 2645cs
dc.identifier.wos000904368000001


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Zobrazit minimální záznam

© 2022 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 © 2022 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.