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Indirect monitoring of machining characteristics via advanced sensor systems: a critical review

International Journal of Advanced Manufacturing Technology · Haziran 2022

YÖKSİS DOI Eşleşmesi Bulundu

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YÖKSİS Kayıtları
Indirect monitoring of machining characteristics via advanced sensor systems: a critical review
The International Journal of Advanced Manufacturing Technology · 2022 SCI-Expanded
Doç. Dr. MUSTAFA KUNTOĞLU →
YÖKSİS ISSN Eşleşmesi

Bu dergide (ISSN eşleşmesi) kurumun 13 kaydı bulundu.

YÖKSİS Kayıtları — ISSN Eşleşmesi
Cost optimization of submersible motors using a genetic algorithm and a finite element method
2007 ISSN: 0268-3768 SCI-Expanded
Prof. Dr. MEHMET ÇUNKAŞ →
Modelling of Dynamic Cutting Force Coefficients and Chatter Stability Dependent on Shear Angle Oscillation
2017 ISSN: 0268-3768 SCI-Expanded
Prof. Dr. SÜLEYMAN NEŞELİ →
A simple approach to analyze process damping in chatter vibration
2014 ISSN: 0268-3768 SCI-Expanded
Prof. Dr. SÜLEYMAN NEŞELİ →
Failure analysis of support during profile cutting process using horizontal milling machine
2014 ISSN: 0268-3768 SCI-Expanded 1 atıf
Prof. Dr. SÜLEYMAN NEŞELİ →
A state-of-the-art review on sensors and signal processing systems in mechanical machining processes
2021 ISSN: 0268-3768 SCI-Expanded Q2
Doç. Dr. EMİN SALUR →
Influence of tool path strategies on machining time, tool wear, and surface roughness during milling of AISI X210Cr12 steel
2022 ISSN: 0268-3768 SCI-Expanded Q2
Dr. Öğr. Üyesi ÜSAME ALİ USCA →
Investigations on tool wear, surface roughness, cutting temperature, and chip formation in machining of Cu-B-CrC composites
2021 ISSN: 0268-3768 SCI-Expanded Q2
Doç. Dr. MUSTAFA KUNTOĞLU →
Influence of tool path strategies on machining time, tool wear, and surface roughness during milling of AISI X210Cr12 steel
2022 ISSN: 0268-3768 SCI Q2
Doç. Dr. MUSTAFA KUNTOĞLU →
Indirect monitoring of machining characteristics via advanced sensor systems: a critical review
2022 ISSN: 0268-3768 SCI-Expanded Q2
Doç. Dr. MUSTAFA KUNTOĞLU →
Tool wear and machinability investigations in dry turning of Cu/Mo-SiCp hybrid composites
2021 ISSN: 0268-3768 SCI-Expanded Q2
Doç. Dr. MUSTAFA KUNTOĞLU →
A state of the art on surface morphology of selective laser-melted metallic alloys
2023 ISSN: 0268-3768 SCI-Expanded Q2
Dr. Öğr. Üyesi EYÜB CANLI →
Theoretical and experimental research of edge inclination angle effect on minimum uncut chip thickness in oblique cutting of C45 steel
2022 ISSN: 0268-3768 SCI-Expanded Q2
Doç. Dr. MUSTAFA KUNTOĞLU →
An investigation of the shearing performance and sheared surface characterisation of ultra-strength DP steel-Al explosive welded plate composite
2023 ISSN: 0268-3768 SCI-Expanded Q2
Prof. Dr. MUSTAFA ACARER →

Makale Bilgileri

Dergi International Journal of Advanced Manufacturing Technology
ISSN02683768
Yayın TarihiHaziran 2022
Cilt / Sayfa120 · 7043-7078
DOI10.1007/s00170-022-09286-x
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
Scimago Dergi (ISSN Eşleşmesi)
International Journal of Advanced Manufacturing Technology
Q1
SJR Skoru0,706
H-Index175
YayıncıSpringer London
ÜlkeUnited Kingdom
Industrial and Manufacturing Engineering (Q1)
Computer Science Applications (Q2)
Control and Systems Engineering (Q2)
Mechanical Engineering (Q2)
Software (Q2)
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Metrikler

81
Atıf
8
Yazar
6
Anahtar Kelime

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