A review of surface integrity in machining of hardened steels

WF Sales, J Schoop, LRR da Silva, ÁR Machado… - Journal of Manufacturing …, 2020 - Elsevier
This paper presents a background of surface integrity in the machining of hardened steels
for rolling dies, moulds, bearings, shafts, gears, etc. Hardened steels, which are normally …

A semi-supervised convolutional neural network-based method for steel surface defect recognition

Y Gao, L Gao, X Li, X Yan - Robotics and Computer-Integrated …, 2020 - Elsevier
Automatic defect recognition is one of the research hotspots in steel production, but most of
the current methods focus on supervised learning, which relies on large-scale labeled …

A new graph-based semi-supervised method for surface defect classification

Y Wang, L Gao, Y Gao, X Li - Robotics and Computer-Integrated …, 2021 - Elsevier
Vision-based defect classification is an important technology to control the quality of product
in manufacturing system. As it is very hard to obtain enough labeled samples for model …

Acoustic feature based geometric defect identification in wire arc additive manufacturing

NA Surovi, GS Soh - Virtual and Physical Prototyping, 2023 - Taylor & Francis
In additive manufacturing of metals, numerous techniques have been employed to sense
print defects. Among these, acoustic-based sensing has the advantage of low cost and …

Selected mathematical optimization methods for solving problems of engineering practice

A Vagaská, M Gombár, Ľ Straka - Energies, 2022 - mdpi.com
Engineering optimization is the subject of interest for many scientific research teams on a
global scale; it is a part of today's mathematical modelling and control of processes and …

Predicting part deformation based on deformation force data using Physics-informed Latent Variable Model

Z Zhao, Y Li, C Liu, X Liu - Robotics and Computer-Integrated …, 2021 - Elsevier
Part deformation prediction and control is a crucial issue for obtaining tight dimensional
accuracy so as to ensure product quality with high performance, and deformation prediction …

An intelligent process parameters determination method based on multi-algorithm fusion: a case study in five-axis milling

Z Wang, S Wang, S Wang, Z Zhao, Q Tang - Robotics and Computer …, 2022 - Elsevier
Process parameters have a significant effect on surface integrity, which determines the
service performance of the parts. To improve surface integrity, the process parameters are …

Semi-supervised learning for steel surface inspection using magnetic flux leakage signal

JE Park, YK Kim - Journal of Intelligent Manufacturing, 2023 - Springer
This paper proposes a semi-supervised learning model for detecting multi-defect
classification and localization on the steel surface for industries with limited labeled …

[HTML][HTML] Experimental design of steel surface defect detection based on MSFE-YOLO—An improved YOLOv5 algorithm with multi-scale feature extraction

L Li, R Zhang, T Xie, Y He, H Zhou, Y Zhang - Electronics, 2024 - mdpi.com
Integrating artificial intelligence (AI) technology into student training programs is strategically
crucial for developing future professionals with both forward-thinking capabilities and …

Surface integrity evaluation of high-strength steel with a TiCN-NbC composite coated tool by dry milling

G Zheng, X Cheng, Y Dong, H Liu, Y Yu - Measurement, 2020 - Elsevier
During high-speed machining (HSM) of high-strength steel, the poor surface integrity of
workpiece affects its service performance. HSM of AISI 4340 steel is carried out by a TiCN …