Product quality prediction, as an important issue of industrial intelligence, is a typical task of
industrial process analysis, in which product quality will be evaluated and improved as …

Neural networks have achieved remarkable success across various fields. However, the
lack of interpretability limits their practical use, particularly in critical decision-making …

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 …

It is desirable in injection moulding that every yielded product is of high quality and
precision. Several studies are conducted on modelling the relationship between the process …

Time series extrinsic regression (TSER) aims at predicting numeric values based on the
knowledge of the entire time series. The key to solving the TSER problem is to extract and …

Deep neural networks (DNNs), especially convolutional neural networks (CNNs), have been
effective in various data-driven applications. Yet, DNNs suffer from several major …

Mining data collected from industrial manufacturing process plays an important role for
intelligent manufacturing in Industry 4.0. In this paper, we propose a deep convolutional …

Large volumes of manufacturing data may now be collected because to the growing
popularity of smart Industry 4.0. Product quality may be predicted from manufacturing data …

Forecasting in production systems is used to anticipate their quality, efficiency, and yield.
However, to the best of our knowledge, there exists no systematic review for industrial fore …

With the development of information technology, a large number of product quality data in
the entire manufacturing process is accumulated, but it is not explored and used effectively …