All Outputs (6)

Investigating multi-level ontology to support manufacturing during demand fluctuation (2023)
Conference Proceeding
Kazantsev, N., Niewiadomski, K., Martínez-Arellano, G., Elshafei, B., Mo, F., & Murthy, S. R. (2023). Investigating multi-level ontology to support manufacturing during demand fluctuation. In Low-Cost Digital Solutions for Industrial Automation (LoDiSA 2023). https://doi.org/10.1049/icp.2023.1752

Responding to demand fluctuations represents a challenge for manufacturers, as they often face resource limitations and cannot assess all potential solutions. This paper presents a low-cost semantic engineering solution (ontology) to coordinate poten... Read More about Investigating multi-level ontology to support manufacturing during demand fluctuation.

Efficient decision-making in SMEs: leveraging knowledge graphs with Neo4j and AI vision (2023)
Conference Proceeding
Mo, F., Ur Rehman, H. U., Elshafei, B., Chaplin, J. C., Sanderson, D., Martínez-Arellano, G., & Ratchev, S. (2023). Efficient decision-making in SMEs: leveraging knowledge graphs with Neo4j and AI vision. In Low-Cost Digital Solutions for Industrial Automation (LoDiSA 2023). https://doi.org/10.1049/icp.2023.1736

In the evolving digital landscape, Small and Medium-sized Enterprises (SMEs) grapple with the intricate task of managing vast manufacturing data while operating within budgetary constraints. Addressing this dichotomy, our research introduces an innov... Read More about Efficient decision-making in SMEs: leveraging knowledge graphs with Neo4j and AI vision.

Enabling Coordinated Elastic Responses of Manufacturing Systems through Semantic Modelling (2023)
Conference Proceeding
Martínez-Arellano, G., Niewiadomski, K., Mo, F., Elshafei, B., Chaplin, J. C., Mcfarlane, D., & Ratchev, S. (2023). Enabling Coordinated Elastic Responses of Manufacturing Systems through Semantic Modelling.

Resilience to supply chain disruptions and to changing product volumes and specifications are currently major challenges for the manufacturing sector. To maintain quality and productivity, manufacturers need to be able to respond to disruption using... Read More about Enabling Coordinated Elastic Responses of Manufacturing Systems through Semantic Modelling.

A Framework for Manufacturing System Reconfiguration based on Artificial Intelligence and Digital Twin (2022)
Conference Proceeding
Mo, F., Chaplin, J. C., Sanderson, D., Rehman, H. U., Monetti, F. M., Maffei, A., & Ratchev, S. (2022). A Framework for Manufacturing System Reconfiguration based on Artificial Intelligence and Digital Twin. In Flexible Automation and Intelligent Manufacturing: The Human-Data-Technology Nexus Proceedings of FAIM 2022, June 19-23, 2022, Detroit, Michigan, USA, Volume 2 (361-373). https://doi.org/10.1007/978-3-031-18326-3_35

The application of digital twins and artificial intelligence to manufacturing has shown potential in improving system resilience, responsiveness, and productivity. Traditional digital twin approaches are generally applied to single, static systems to... Read More about A Framework for Manufacturing System Reconfiguration based on Artificial Intelligence and Digital Twin.

Service Based Approach to Asset Administration Shell for Controlling Testing Processes in Manufacturing (2022)
Conference Proceeding
Rehman, H. U., Chaplin, J. C., Zarzycki, L., Mo, F., Jones, M., & Ratchev, S. (2022). Service Based Approach to Asset Administration Shell for Controlling Testing Processes in Manufacturing. In 10th IFAC Conference On Manufacturing Modelling, Management And Control

The rise in demand for customised products and lower costs has generated the need for incorporating intelligence in production systems. Intelligence is the main driver for enabling intelligent control in production systems to meet feature, part and c... Read More about Service Based Approach to Asset Administration Shell for Controlling Testing Processes in Manufacturing.

Cloud Based Decision Making for Multi-Agent Production Systems (2021)
Conference Proceeding
Rehman, H. U., Pulikottil, T., Estrada-Jimenez, L. A., Mo, F., Chaplin, J. C., Barata, J., & Ratchev, S. (2021). Cloud Based Decision Making for Multi-Agent Production Systems. In Progress in Artificial Intelligence (673-686). https://doi.org/10.1007/978-3-030-86230-5_53

The use of multi-agent systems (MAS) as a distributed control method for shop-floor manufacturing control applications has been extensively researched. MAS provides new implementation solutions for smart manufacturing requirements such as the high dy... Read More about Cloud Based Decision Making for Multi-Agent Production Systems.