Abstract Machine learning has numerous advantages, especially in the rapid digitization of
the manufacturing industry that combines data from manufacturing processes and quality …

Tool wear is intimately related to intelligent operation and maintenance of automated
production, workpiece surface quality, dimension accuracy, and tool life. Therefore, it is …

Abstract Tool Wear Monitoring (TWM) plays a vital role in safeguarding product quality and
enhancing machining efficiency. TWM technology mainly includes physics-based models …

The application of tannic acid (TA) as reinforcement material in cement composites can
effectively improve its sustainable development. Nevertheless, the efficacy of TA can be …

Index-value, or so-called n-value prediction is of paramount importance for understanding
the superconductors' behaviour specially when modeling of superconductors is needed …

The efficient monitoring of tool wear is crucial in ensuring precise part manufacturing and
enhancing machining efficiency during the cutting process. However, the presence of …

Carrier separation efficiency significantly impacts the photocatalyst performance for
wastewater purification. However, there is no established theory to accurately guide carrier …

With a view to further realising the intelligence of tool condition monitoring (TCM) and to
address the high cost and low stiffness problems of existing smart tool holders, this study …

In this study, a new method has been developed using Convolutional Neural Networks
(CNN) and Support Vector Regression (SVR) integration to determine the compressive …

In recent years, tool condition monitoring (TCM) based on deep learning has been widely
considered and achieved remarkable success. However, these methods typically require …