Recent advances in artificial intelligence in general, and deep learning in particular, enable
innovations that have a massive impact on society and industries. Autonomous driving …

Tool wear is a cost driver in the metal cutting industry. Besides costs for the cutting tools
themselves, further costs appear-equipment downtime for tool changes, reworking of …

Rapid and accurate industrial inspection to ensure the highest quality standards at a
competitive price is one of the biggest challenges in the manufacturing industry. This paper …

Deep learning has emerged as a state-of-the-art learning technique across a wide range of
applications, including image recognition, object detection and localisation, natural …

The manufacturing sector is envisioned to be heavily influenced by artificial-intelligence-
based technologies with the extraordinary increases in computational power and data …

Data-driven methods provided smart manufacturing with unprecedented opportunities to
facilitate the transition toward Industry 4.0–based production. Machine learning and deep …

Deep learning-based data-driven methods have been successfully developed in tool wear
condition monitoring (TWCM), relying on the massive available labeled samples and the …

Tool condition monitoring and machine tool diagnostics are performed using advanced
sensors and computational intelligence to predict and avoid adverse conditions for cutting …

The growing application of data-driven analytics in materials science has led to the rise of
materials informatics. Within the arena of data analytics, deep learning has emerged as a …

Tool condition monitoring is critical in ultraprecision manufacturing in order to optimize the
performance of the overall process, while maintaining the desired part quality. Recently …