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 …

[HTML][HTML] Infrastructure monitoring and quality diagnosis in CNC machining: A review

M Ntemi, S Paraschos, A Karakostas… - CIRP Journal of …, 2022 - Elsevier
Infrastructure monitoring and rapid quality diagnosis comprise the key solutions to achieve
zero-defect smart manufacturing. The most fundamental systems in manufacturing industries …

Prediction of soil liquefaction for railway embankment resting on fine soil deposits using enhanced machine learning techniques

S Ghani, S Kumari - Journal of Earth System Science, 2023 - Springer
As a key mass transit system, railroad projects have recently taken on a significant role in
urban mobility. Due to their relative importance, examining how stable these projects are in …

Thermal error modeling of machine tool based on dimensional error of machined parts in automatic production line

H Shi, Y Xiao, X Mei, T Tao, H Wang - ISA transactions, 2023 - Elsevier
Thermally induced error has proven to be the major source of machining error for the
machine tool working in a non-temperature-controlled workshop. Current research on …

Acoustic emission monitoring of sawing process: artificial intelligence approach for optimal sensory feature selection

V Nasir, J Cool, F Sassani - The International Journal of Advanced …, 2019 - Springer
A methodology is presented for acoustic emission (AE) monitoring of Douglas fir wood in
circular sawing process under extreme cutting conditions. An AE sensor was mounted on …

[HTML][HTML] AI-based optimisation of total machining performance: A review

K Ullrich, M von Elling, K Gutzeit, M Dix… - CIRP Journal of …, 2024 - Elsevier
Advanced modelling and optimisation techniques have been widely used in recent years to
enable intelligent manufacturing and digitalisation of manufacturing processes. In this …

Development of an intelligent model to optimize heat-affected zone, kerf, and roughness in 309 stainless steel plasma cutting by using experimental results

S Masoudi, M Mirabdolahi, M Dayyani… - Materials and …, 2019 - Taylor & Francis
Plasma cutting is an effective way to cut hard metals. In this process, three output
parameters cutting width (kerf), surface roughness (Ra) and heat-affected zone (HAZ) are …

[HTML][HTML] Environmental sustenance via melon seed peel conversion to fermentable sugars using soft computing models

K Nwosu-Obieogu, GW Dzarma, C Ugwuodo… - Cleaner Engineering …, 2022 - Elsevier
There is a shift in focus on agro-wastes constituting menace through their disposal in the
environment by converting them to value-added products within the sustainability …

Novel Framework for Quality Control in Vibration Monitoring of CNC Machining

G Apostolou, M Ntemi, S Paraschos, I Gialampoukidis… - Sensors, 2024 - mdpi.com
Vibrations are a common issue in the machining and metal-cutting sector, in which the
spindle vibration is primarily responsible for the poor surface quality of workpieces. The …

Modeling of cutting parameters in turning of PEEK composite using artificial neural networks and adaptive-neural fuzzy inference systems

G Özden, MÖ Öteyaka… - Journal of Thermoplastic …, 2023 - journals.sagepub.com
Polyetheretherketone (PEEK) and its composites are commonly used in the industry.
Materials with PEEK are widely used in aeronautical, automotive, mechanical, medical …