| Makale Türü |
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| Makale Alt Türü | SCI, SSCI, AHCI, SCI-Exp dergilerinde yayınlanan teknik not, editöre mektup, tartışma, vaka takdimi ve özet türünden makale |
| Dergi Adı | Arabian Journal for Science and Engineering |
| Dergi ISSN | 2193-567X Wos Dergi Scopus Dergi |
| Dergi Tarandığı Indeksler | SCI-Expanded |
| Dergi Grubu | Q2 |
| Makale Dili | Türkçe |
| Basım Tarihi | 06-2024 |
| Cilt No | 49 |
| Sayı | 8 |
| Sayfalar | 10287 / 10326 |
| DOI Numarası | 10.1007/s13369-024-09163-7 |
| Makale Linki | 10.1007/s13369-024-09163-7 |
| Özet |
| Information 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 … |
| Anahtar Kelimeler |
| Analytical modeling | Chip formation | Cutting force | Machining | Modeling approaches |
| Dergi Adı | ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING |
| Yayıncı | Springer Nature |
| Açık Erişim | Hayır |
| ISSN | 2193-567X |
| E-ISSN | 2191-4281 |
| CiteScore | 6,5 |
| SJR | 0,521 |
| SNIP | 1,003 |