All Outputs (7)

Immune system inspired smart maintenance framework: tool wear monitoring use case (2024)
Journal Article
Pulikottil, T., Martínez-Arellano, G., & Barata, J. (2024). Immune system inspired smart maintenance framework: tool wear monitoring use case. International Journal of Advanced Manufacturing Technology, 132(9-10), 4699-4721. https://doi.org/10.1007/s00170-024-13472-4

As the manufacturing industry is moving towards the fourth industrial revolution, there is an increasing need for smart maintenance systems that could provide manufacturers with a competitive advantage by predicting failures. Despite various efforts... Read More about Immune system inspired smart maintenance framework: tool wear monitoring use case.

Classification of cancer cells at the sub-cellular level by phonon microscopy using deep learning (2023)
Journal Article
Pérez-Cota, F., Martínez-Arellano, G., La Cavera III, S., Hardiman, W., Thornton, L., Fuentes-Domínguez, R., …Clark, M. (2023). Classification of cancer cells at the sub-cellular level by phonon microscopy using deep learning. Scientific Reports, 13, Article 16228. https://doi.org/10.1038/s41598-023-42793-9

There is a consensus about the strong correlation between the elasticity of cells and tissue and their normal, dysplastic, and cancerous states. However, developments in cell mechanics have not seen significant progress in clinical applications. In t... Read More about Classification of cancer cells at the sub-cellular level by phonon microscopy using deep learning.

Semantic models and knowledge graphs as manufacturing system reconfiguration enablers (2023)
Journal Article
Mo, F., Chaplin, J. C., Sanderson, D., Martínez-Arellano, G., & Ratchev, S. (2024). Semantic models and knowledge graphs as manufacturing system reconfiguration enablers. Robotics and Computer-Integrated Manufacturing, 86, Article 102625. https://doi.org/10.1016/j.rcim.2023.102625

Reconfigurable Manufacturing System (RMS) provides a cost-effective approach for manufacturers to adapt to fluctuating market demands by reconfiguring assets through automated analysis of asset utilization and resource allocation. Achieving this auto... Read More about Semantic models and knowledge graphs as manufacturing system reconfiguration enablers.

A data analytics model for improving process control in flexible manufacturing cells (2022)
Journal Article
Martínez-Arellano, G., Nguyen, T., Hinton, C., & Ratchev, S. (2022). A data analytics model for improving process control in flexible manufacturing cells. Decision Analytics Journal, 3, Article 100075. https://doi.org/10.1016/j.dajour.2022.100075

With the need of more responsive and resilient manufacturing processes for high value, customised products, Flexible Manufacturing Systems (FMS) remain a very relevant manufacturing approach. Due to their complexity, quality monitoring in these types... Read More about A data analytics model for improving process control in flexible manufacturing cells.

XOR Binary Gravitational Search Algorithm with Repository: Industry 4.0 Applications (2020)
Journal Article
Ahmadieh Khanesar, M., Bansal, R., Martínez-Arellano, G., & Branson, D. (2020). XOR Binary Gravitational Search Algorithm with Repository: Industry 4.0 Applications. Applied Sciences, 10(8), Article 6451. https://doi.org/10.3390/app10186451

Industry 4.0 is the fourth generation of industry which will theoretically revolutionize manufacturing methods through the integration of machine learning and artificial intelligence approaches on the factory floor to obtain robustness and sped-up pr... Read More about XOR Binary Gravitational Search Algorithm with Repository: Industry 4.0 Applications.

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.

Creating AI Characters for Fighting Games Using Genetic Programming (2016)
Journal Article
Martinez-Arellano, G., Cant, R., & Woods, D. (2017). Creating AI Characters for Fighting Games Using Genetic Programming. IEEE Transactions on Computational Intelligence and AI in Games, 9(4), 423-434. https://doi.org/10.1109/tciaig.2016.2642158

This paper proposes a character generation approach for the M.U.G.E.N. fighting game that can create engaging AI characters using a computationally cheap process without the intervention of the expert developer. The approach uses a genetic programmin... Read More about Creating AI Characters for Fighting Games Using Genetic Programming.