Understanding of machine learning with deep learning: architectures, workflow, applications and future directions

MM Taye - Computers, 2023 - mdpi.com
In recent years, deep learning (DL) has been the most popular computational approach in
the field of machine learning (ML), achieving exceptional results on a variety of complex …

Artificial intelligence systems for tool condition monitoring in machining: Analysis and critical review

DY Pimenov, A Bustillo, S Wojciechowski… - Journal of Intelligent …, 2023 - Springer
The wear of cutting tools, cutting force determination, surface roughness variations and other
machining responses are of keen interest to latest researchers. The variations of these …

Machine learning and deep learning based predictive quality in manufacturing: a systematic review

H Tercan, T Meisen - Journal of Intelligent Manufacturing, 2022 - Springer
With the ongoing digitization of the manufacturing industry and the ability to bring together
data from manufacturing processes and quality measurements, there is enormous potential …

[HTML][HTML] Condition monitoring using machine learning: A review of theory, applications, and recent advances

O Surucu, SA Gadsden, J Yawney - Expert Systems with Applications, 2023 - Elsevier
In modern industry, the quality of maintenance directly influences equipment's operational
uptime and efficiency. Hence, based on monitoring the condition of the machinery, predictive …

[HTML][HTML] Machine learning and artificial intelligence in CNC machine tools, a review

M Soori, B Arezoo, R Dastres - Sustainable Manufacturing and Service …, 2023 - Elsevier
Abstract Artificial Intelligence (AI) and Machine learning (ML) represents an important
evolution in computer science and data processing systems which can be used in order to …

Systematic review on tool breakage monitoring techniques in machining operations

X Li, X Liu, C Yue, SY Liang, L Wang - International Journal of Machine …, 2022 - Elsevier
Tool condition monitoring (TCM) in machining operations is crucial to maximise the useful
tool life while reducing the risks associated with tool breakage. Unlike progressive tool wear …

Deep reinforcement learning in production systems: a systematic literature review

M Panzer, B Bender - International Journal of Production Research, 2022 - Taylor & Francis
Shortening product development cycles and fully customisable products pose major
challenges for production systems. These not only have to cope with an increased product …

A review of indirect tool condition monitoring systems and decision-making methods in turning: Critical analysis and trends

M Kuntoğlu, A Aslan, DY Pimenov, ÜA Usca, E Salur… - Sensors, 2020 - mdpi.com
The complex structure of turning aggravates obtaining the desired results in terms of tool
wear and surface roughness. The existence of high temperature and pressure make difficult …

A review on deep learning in machining and tool monitoring: Methods, opportunities, and challenges

V Nasir, F Sassani - The International Journal of Advanced Manufacturing …, 2021 - Springer
Data-driven methods provided smart manufacturing with unprecedented opportunities to
facilitate the transition toward Industry 4.0–based production. Machine learning and deep …

Future research directions in the machining of Inconel 718

A De Bartolomeis, ST Newman, IS Jawahir… - Journal of Materials …, 2021 - Elsevier
Inconel 718 is the most popular nickel-based superalloy, extensively used in aerospace,
automotive and energy industries owing to its extraordinary thermomechanical properties. It …