This article reviews and analyzes the approaches utilized for monitoring cutting tool
conditions. The Research focuses on publications from 2012 to 2022 (10 years), in which …

Tool wear, closely linked to operational efficiency and economic viability, must be detected
and managed promptly to prevent significant losses. Traditional methods for tool wear …

Tool wear condition monitoring plays a crucial role in intelligent manufacturing systems to
enhance machining quality and efficiency. The indirect methods employ various sensor …

Remaining useful life (RUL) prediction, as an essential aspect of condition-based
maintenance (CBM), has attracted substantial interest in industrial measurement. Recently …

In the era of Industry 3.0, product fault detection systems became important auxiliary systems
for factories. These systems efficiently monitor product quality, and as such, substantial …

The means of accurately determining tool-wear status has long been important to
manufacturers. Tool-wear status classification enables factories to avoid the unnecessary …

For the application of deep learning (DL) models in the field of remaining useful life (RUL)
prediction and predictive maintenance (PdM) of complex equipment, the insufficient training …

Accurate tool wear state identification models are essential to ensure manufacturing
reliability and efficiency. Tool wear state recognition systems establish a mapping …

The accurate and rapid transfer of complex urban spatio-temporal data is crucial for urban
computing tasks such as urban planning and public transportation deployment for smart-city …

摘要近年来, 复杂制造系统及其自动化, 智能化和定制化等优势在汽车制造, 芯片制造,
机器人等领域得到了广泛关注, 其建模与优化问题也已成为国内外的研究热点 …