Mrs GIOVANNA MARTINEZ ARELLANO's Outputs (2)

Tool Wear Classification using Time Series Imaging and Deep Learning (2019)
Journal Article
Martínez-Arellano, G., Terrazas, G., & Ratchev, S. (2019). Tool Wear Classification using Time Series Imaging and Deep Learning. International Journal of Advanced Manufacturing Technology, 104(9-12), 3647–3662. https://doi.org/10.1007/s00170-019-04090-6

Tool Condition Monitoring (TCM) has become essential to achieve high quality machining as well as cost-effective production. Identification of the cutting tool state during machining before it reaches its failure stage is critical. This paper present... Read More about Tool Wear Classification using Time Series Imaging and Deep Learning.

Towards an active learning approach to tool condition monitoring with Bayesian deep learning (2019)
Presentation / Conference Contribution
Martinez Arellano, G., & Ratchev, S. (2019, June). Towards an active learning approach to tool condition monitoring with Bayesian deep learning. Presented at ECMS 2019: 33rd International ECMS Conference on Modelling and Simulation

With the current advances in the Internet of Things (IoT), smart sensors and Artificial Intelligence (AI), a new generation of condition monitoring solutions for smart manufacturing is starting to emerge. Computer Numerical Control (CNC) machines can... Read More about Towards an active learning approach to tool condition monitoring with Bayesian deep learning.