A state-of-the-art review on sensors and signal processing systems in mechanical machining processes

M Kuntoğlu, E Salur, MK Gupta, M Sarıkaya… - … International Journal of …, 2021 - Springer
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 …

A critical review on applications of artificial intelligence in manufacturing

O Mypati, A Mukherjee, D Mishra, SK Pal… - Artificial Intelligence …, 2023 - Springer
The fourth industrial revolution, Industry 4.0, has brought internet, artificial intelligence (AI),
and machine learning (ML) concepts into manufacturing. There is an immediate need to …

Process monitoring of machining

R Teti, D Mourtzis, DM D'Addona, A Caggiano - CIRP Annals, 2022 - Elsevier
This keynote paper mainly focuses on advancements of machining technology and systems
for enhanced performance, increased system integration and augmented machine …

Combining translation-invariant wavelet frames and convolutional neural network for intelligent tool wear state identification

XC Cao, BQ Chen, B Yao, WP He - Computers in Industry, 2019 - Elsevier
On-machine monitoring of tool wear in machining processes has found its importance to
reduce equipment downtime and reduce tooling costs. As the tool wears out gradually, the …

Tool condition monitoring using spectral subtraction and convolutional neural networks in milling process

F Aghazadeh, A Tahan, M Thomas - The International Journal of …, 2018 - Springer
Process monitoring is necessary in machining operation to increase productivity, improve
surface quality, and reduce unscheduled downtime. Tool wear and breakage are important …

Tool wear monitoring of a retrofitted CNC milling machine using artificial neural networks

DF Hesser, B Markert - Manufacturing letters, 2019 - Elsevier
Predictive maintenance, in contrast to preventive maintenance, raises the manufacturing
quality and reliability, where the integrity is monitored continuously in service. To prevent …

Review on prognostics and health management in smart factory: From conventional to deep learning perspectives

P Kumar, I Raouf, HS Kim - Engineering Applications of Artificial …, 2023 - Elsevier
At present, the fourth industrial revolution is pushing factories toward an intelligent,
interconnected grid of machinery, communication systems, and computational resources …

Prediction of cutting tool wear during milling process using artificial intelligence techniques

S Shankar, T Mohanraj, R Rajasekar - International Journal of …, 2019 - Taylor & Francis
An efficient tool condition monitoring system was designed for keyway milling of 7075-T6
hybrid aluminium alloy composite with resultant machining force and sound acquired while …

Tool wear prediction in hard turning of EN8 steel using cutting force and surface roughness with artificial neural network

T SK, S Shankar, DK - Proceedings of the Institution of …, 2020 - journals.sagepub.com
In this work, the flank wear of the cutting tool is predicted using artificial neural network
based on the responses of cutting force and surface roughness. EN8 steel is chosen as a …

Machine health management in smart factory: A review

GY Lee, M Kim, YJ Quan, MS Kim, TJY Kim… - Journal of Mechanical …, 2018 - Springer
In this paper, we present a review of machine health managements for the smart factory. As
the Industry 4.0 leads current factory automation and intelligent machines, the machine …