A state-of-the-art review on sensors and signal processing systems in mechanical machining processes
Yazarlar (5)
Doç. Dr. Mustafa Kuntoğlu Selçuk Üniversitesi, Türkiye
Doç. Dr. Emin Salur Selçuk Üniversitesi, Türkiye
Munish Kumar Gupta
Opole University Of Technology, Polonya
Opole University Of Technology, Polonya
Prof. Dr. Murat SARIKAYA Sinop Üniversitesi, Türkiye
Danil Yu Pimenov
South Ural State University, Rusya Federasyonu
South Ural State University, Rusya Federasyonu
| 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) | ||
| Dergi Adı | International Journal of Advanced Manufacturing Technology (Q2) | ||
| Dergi ISSN | 0268-3768 Dergi Bilgileri (2021) | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | Türkçe | Basım Tarihi | 01-2021 |
| Cilt / Sayı / Sayfa | 116 / 9 / 2711–2735 | DOI | 10.1007/s00170-021-07425-4 |
| Makale Linki | http://dx.doi.org/10.1007/s00170-021-07425-4 | ||
| UAK Araştırma Alanları |
Üretim Teknolojileri
|
||
| Özet |
| Sensors are the main equipment of the data-based enterprises for diagnosis of the health of system. Offering time- or frequency-dependent systemic information provides prognosis with the help of early-warning system using intelligent signal processing systems. Therefore, a chain of data-based information improves the efficiency especially focusing on the determination of remaining useful life of a machine or tool. A broad utilization of sensors in machining processes and artificial intelligence–supported data analysis and signal processing systems are prominent technological tools in the way of Industry 4.0. Therefore, this paper outlines the state of the art of the mentioned systems encountered in the open literature. As a result, existing studies using sensor systems including signal processing facilities in machining processes provide important contribution for error minimization and productivity maximization … |
| Anahtar Kelimeler |
| Artificial intelligence | Industry 4.0 | Machining | Sensors: signal processing |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 94 |
| Scopus | 120 |
| Google Scholar | 1 |
| Google Scholar | 152 |