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

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dc.authoridSarikaya, Murat/0000-0001-6100-0731
dc.authoridPehlivan, Fatih/0000-0003-2675-6124
dc.authoridKORKMAZ, Mehmet Erdi/0000-0002-0481-6002
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.accessioned2025-03-23T19:42:20Z
dc.date.available2025-03-23T19:42:20Z
dc.date.issued2024
dc.departmentSinop Üniversitesi
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.
dc.description.sponsorshipKarabk niversitesi
dc.description.sponsorshipNo Statement Available
dc.identifier.doi10.1007/s13369-024-09163-7
dc.identifier.endpage10326
dc.identifier.issn2193-567X
dc.identifier.issn2191-4281
dc.identifier.issue8
dc.identifier.scopus2-s2.0-85195522959
dc.identifier.scopusqualityQ1
dc.identifier.startpage10287
dc.identifier.urihttps://doi.org/10.1007/s13369-024-09163-7
dc.identifier.urihttps://hdl.handle.net/11486/6766
dc.identifier.volume49
dc.identifier.wosWOS:001243342000002
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSpringer Heidelberg
dc.relation.ispartofArabian Journal For Science and Engineering
dc.relation.publicationcategoryDiğer
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WOS_20250323
dc.subjectChip formation
dc.subjectCutting force
dc.subjectMachining
dc.subjectModeling approaches
dc.subjectAnalytical modeling
dc.titleAnalytical Modeling Methods in Machining: A State of the Art on Application, Recent Challenges, and Future Trends
dc.typeReview

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