Scopus
YÖKSİS Eşleşti
Indirect monitoring of machining characteristics via advanced sensor systems: a critical review
International Journal of Advanced Manufacturing Technology · Haziran 2022
YÖKSİS Kayıtları
Indirect monitoring of machining characteristics via advanced sensor systems: a critical review
The International Journal of Advanced Manufacturing Technology · 2022 SCI-Expanded
DOÇENT MUSTAFA KUNTOĞLU →
Makale Bilgileri
DergiInternational Journal of Advanced Manufacturing Technology
Yayın TarihiHaziran 2022
Cilt / Sayfa120 · 7043-7078
Scopus ID2-s2.0-85129513519
Özet
On-line monitoring of the machining processes provides to detect the amount and type of tool wear which is critical for the determination of remaining useful lifetime of cutting tool. According to Industry 4.0 revolution, the machining performance in terms of cutting forces, surface roughness, power consumptions, tool wear, tool life, etc. needs to be automatically monitored because the unfavorable conditions in machining cause chatter vibrations, tool breakage, and dimensional accuracy. Therefore, the usage of advanced sensor systems plays a key role in achieving the improved machining characteristics in terms of less human effort, errors, production time, etc. and fulfills the requirement of Industry 4.0. Hence, this review presents the holistic knowledge of online detection systems including sensors and signal processing software preferred in mechanical machining operations. Initially, this paper is starting with the up-to-date literature introduction section followed by type of sensors used in machining, online detection methods in machining, challenges and suggestions, etc. Eventually, the article concluded the findings and future remarks especially focused on the theme of Industry 4.0. In the end, it is worthy to mention that this review paper is very helpful for researchers and academicians working in the industrial sectors.
Yazarlar (8)
1
Mehmet Erdi Korkmaz
2
Munish Kumar Gupta
ORCID: 0000-0002-0777-1559
3
Zhixiong Li
4
Grzegorz M. Krolczyk
5
Mustafa Kuntoğlu
ORCID: 0000-0002-7291-9468
6
Rüstem Binali
ORCID: 0000-0003-0775-3817
7
Nafiz Yaşar
8
Danil Yurievich Pimenov
Anahtar Kelimeler
Cutting forces
Industry 4.0
Sensors
Signal processing
Tool monitoring
Tool wear
Kurumlar
Karabük Üniversitesi
Karabuk Turkey
Opole University of Technology
Opole Poland
Selçuk Üniversitesi
Selçuklu Turkey
South Ural State University
Chelyabinsk Russian Federation
Metrikler
53
Atıf
8
Yazar
6
Anahtar Kelime