Analytical Modeling Methods in Machining: A State of the Art on Application, Recent Challenges, and Future Trends

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dc.authoridPehlivan, Fatih/0000-0003-2675-6124
dc.authoridKORKMAZ, Mehmet Erdi/0000-0002-0481-6002
dc.authoridSarikaya, Murat/0000-0001-6100-0731
dc.authoridGupta, Munish/0000-0002-0777-1559
dc.contributor.authorKorkmaz, Mehmet Erdi
dc.contributor.authorGupta, Munish Kumar
dc.contributor.authorSarikaya, Murat
dc.contributor.authorGunay, Mustafa
dc.contributor.authorBoy, Mehmet
dc.contributor.authorYasar, Nafiz
dc.contributor.authorDemirsoz, Recep
dc.date.accessioned2024-09-29T15:54:44Z
dc.date.available2024-09-29T15:54:44Z
dc.date.issued2024
dc.departmentKarabük Üniversitesien_US
dc.description.abstractInformation technology applications are crucial to the proper utilization of manufacturing equipment in the new industrial age, i.e., Industry 4.0. There are certain fundamental conditions that users must meet to adapt the manufacturing processes to Industry 4.0. For this, as in the past, there is a major need for modeling and simulation tools in this industrial age. In the creation of industry-driven predictive models for machining processes, substantial progress has recently been made. This paper includes a comprehensive review of predictive performance models for machining (particularly analytical models), as well as a list of existing models' strengths and drawbacks. It contains a review of available modeling tools, as well as their usability and/or limits in the monitoring of industrial machining operations. The goal of process models is to forecast principal variables such as stress, strain, force, and temperature. These factors, however, should be connected to performance outcomes, i.e., product quality and manufacturing efficiency, to be valuable to the industry (dimensional accuracy, surface quality, surface integrity, tool life, energy consumption, etc.). Industry adoption of cutting models depends on a model's ability to make this connection and predict the performance of process outputs. Therefore, this review article organizes and summarizes a variety of critical research themes connected to well-established analytical models for machining processes.en_US
dc.description.sponsorshipKarabk niversitesien_US
dc.description.sponsorshipNo Statement Availableen_US
dc.identifier.doi10.1007/s13369-024-09163-7
dc.identifier.endpage10326en_US
dc.identifier.issn2193-567X
dc.identifier.issn2191-4281
dc.identifier.issue8en_US
dc.identifier.scopus2-s2.0-85195522959en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage10287en_US
dc.identifier.urihttps://doi.org/10.1007/s13369-024-09163-7
dc.identifier.urihttps://hdl.handle.net/20.500.14619/4246
dc.identifier.volume49en_US
dc.identifier.wosWOS:001243342000002en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer Heidelbergen_US
dc.relation.ispartofArabian Journal For Science and Engineeringen_US
dc.relation.publicationcategoryDiğeren_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectChip formationen_US
dc.subjectCutting forceen_US
dc.subjectMachiningen_US
dc.subjectModeling approachesen_US
dc.subjectAnalytical modelingen_US
dc.titleAnalytical Modeling Methods in Machining: A State of the Art on Application, Recent Challenges, and Future Trendsen_US
dc.typeReviewen_US

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