Analytical Modeling Methods in Machining: A State of the Art on Application, Recent Challenges, and Future Trends
Yazarlar (8)
Doç. Dr. Mehmet Erdi Korkmaz Karabük Üniversitesi, Türkiye
Munish Kumar Gupta
Opole University Of Technology, Polonya
Opole University Of Technology, Polonya
Prof. Dr. Murat SARIKAYA Sinop Üniversitesi, Türkiye
Mustafa Günay Karabük Üniversitesi, Türkiye
Mehmet Boy Sinop Üniversitesi, Türkiye
Doç. Dr. Nafiz Yaşar Dumlupinar Üniversitesi, Türkiye
Recep Demirsöz Karabük Üniversitesi, Türkiye
Fatih Pehlivan Karabük Üniversitesi, Türkiye
| Makale Türü |
Diğer (Teknik, not, yorum, vaka takdimi, editöre mektup, özet, kitap krıtiği,
araştırma notu, bilirkişi raporu ve benzeri)
(SCI, SSCI, AHCI, SCI-Exp dergilerinde yayınlanan teknik not,
editöre mektup, tartışma, vaka takdimi ve özet türünden makale)
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| Dergi Adı | Arabian Journal for Science and Engineering (Q2) | ||
| Dergi ISSN | 2193-567X Dergi Bilgileri (2024) | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | Türkçe | Basım Tarihi | 06-2024 |
| Cilt / Sayı / Sayfa | 49 / 8 / 10287–10326 | DOI | 10.1007/s13369-024-09163-7 |
| Makale Linki | https://doi.org/10.1007/s13369-024-09163-7 | ||
| UAK Araştırma Alanları |
Üretim Teknolojileri
Triboloji
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| 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 |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 6 |
| Scopus | 10 |
| Google Scholar | 16 |