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 …

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 …

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 …

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 …

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 …

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 …

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 …

This paper proposes a semi-supervised learning model for detecting multi-defect
classification and localization on the steel surface for industries with limited labeled …

Nowadays, Automatic metal surface defect recognition is an important research direction in
the field of surface defect recognition, and more convolution neural network algorithms are …