All Outputs (10)

Optimal Manufacturing Configuration Selection: Sequential Decision Making and Optimization using Reinforcement Learning (2023)
Journal Article
Torayev, A., Abadia, J. J. P., Martínez-Arellano, G., Cuesta, M., Chaplin, J. C., Larrinaga, F., …Ratchev, S. (2023). Optimal Manufacturing Configuration Selection: Sequential Decision Making and Optimization using Reinforcement Learning. Procedia CIRP, 120, 986-991. https://doi.org/10.1016/j.procir.2023.09.112

In manufacturing, different costs must be considered when selecting the optimal manufacturing configuration. Costs include manufacturing costs, material costs, labor costs, and overhead costs. Optimal manufacturing configurations are those that minim... Read More about Optimal Manufacturing Configuration Selection: Sequential Decision Making and Optimization using Reinforcement Learning.

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.

Online and Modular Energy Consumption Optimization of Industrial Robots (2023)
Journal Article
Torayev, A., Martinez-Arellano, G., Chaplin, J. C., Sanderson, D., & Ratchev, S. (2024). Online and Modular Energy Consumption Optimization of Industrial Robots. IEEE Transactions on Industrial Informatics, 20(2), 1198-1207. https://doi.org/10.1109/TII.2023.3272692

Industrial robots contribute to a considerable amount of energy consumption in manufacturing. However, modeling the energy consumption of industrial robots is a complex problem as it requires considering components such as the robot controller, fans... Read More about Online and Modular Energy Consumption Optimization of Industrial Robots.

Capacity Modelling and Measurement for Smart Elastic Manufacturing Systems (2023)
Journal Article
Elshafei, B., Mo, F., Chaplin, J. C., Arellano, G. M., & Ratchev, S. (2023). Capacity Modelling and Measurement for Smart Elastic Manufacturing Systems. SAE Technical Papers, Article 2023-01-0997. https://doi.org/10.4271/2023-01-0997

Aerospace manufacturing is improving its productivity and growth by expanding its capacity for production by investing in new tools and more equipment to provide additional capacity and flexibility in the face of widespread supply disruptions and unp... Read More about Capacity Modelling and Measurement for Smart Elastic Manufacturing Systems.

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.

Towards Modular and Plug-and-Produce Manufacturing Apps (2022)
Journal Article
Torayev, A., Martínez-Arellano, G., Chaplin, J. C., Sanderson, D., & Ratchev, S. (2022). Towards Modular and Plug-and-Produce Manufacturing Apps. Procedia CIRP, 107, 1257-1262. https://doi.org/10.1016/j.procir.2022.05.141

Industry 4.0 redefines manufacturing systems as smart and connected systems where software solutions provide additional capabilities to the manufacturing equipment. However, the connection of manufacturing equipment with software solutions is challen... Read More about Towards Modular and Plug-and-Produce Manufacturing Apps.

Towards Flexible, Fault Tolerant Hardware Service Wrappers for the Digital Manufacturing on a Shoestring Project (2020)
Journal Article
McNally, M. J., Chaplin, J. C., Martinez-Arellano, G., & Ratchev, S. (2020). Towards Flexible, Fault Tolerant Hardware Service Wrappers for the Digital Manufacturing on a Shoestring Project. IFAC-PapersOnLine, 53(3), 72-77. https://doi.org/10.1016/j.ifacol.2020.11.065

The adoption of digital manufacturing in small to medium enterprises (SMEs) in the manufacturing sector in the UK is low, yet these technologies offer significant promise to boost productivity. Two major causes of this lack of uptake is the high upfr... Read More about Towards Flexible, Fault Tolerant Hardware Service Wrappers for the Digital Manufacturing on a Shoestring Project.

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.