All Outputs (15)

A modular artificial intelligence and asset administration shell approach to streamline testing processes in manufacturing services (2023)
Journal Article
Rehman, H. U., Mo, F., Chaplin, J. C., Zarzycki, L., Jones, M., & Ratchev, S. (2024). A modular artificial intelligence and asset administration shell approach to streamline testing processes in manufacturing services. Journal of Manufacturing Systems, 72, 424-436. https://doi.org/10.1016/j.jmsy.2023.12.004

The increasing demand for personalized products and cost-effectiveness has highlighted the necessity of integrating intelligence into production systems. This integration is crucial for enabling intelligent control that can adapt to variations in fea... Read More about A modular artificial intelligence and asset administration shell approach to streamline testing processes in manufacturing services.

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.

PLC orchestration automation to enhance human–machine integration in adaptive manufacturing systems (2023)
Journal Article
Mo, F., Ugarte Querejeta, M., Hellewell, J., Rehman, H. U., Illarramendi Rezabal, M., Chaplin, J. C., …Ratchev, S. (2023). PLC orchestration automation to enhance human–machine integration in adaptive manufacturing systems. Journal of Manufacturing Systems, 71, 172-187. https://doi.org/10.1016/j.jmsy.2023.07.015

Current approaches to manufacturing must evolve to respond to increasing demands for short product life cycles and customised products. Adaptive manufacturing systems integrate advanced technologies, automation, and data-driven methodologies to devel... Read More about PLC orchestration automation to enhance human–machine integration in adaptive manufacturing systems.

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.

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.

Agent-based manufacturing — review and expert evaluation (2023)
Journal Article
Pulikottil, T., Estrada-Jimenez, L. A., Ur Rehman, H., Mo, F., Nikghadam-Hojjati, S., & Barata, J. (2023). Agent-based manufacturing — review and expert evaluation. International Journal of Advanced Manufacturing Technology, 127(5-6), 2151-2180. https://doi.org/10.1007/s00170-023-11517-8

The advent of smart manufacturing and the exposure to a new generation of technological enablers have revolutionized the way manufacturing process is carried out. Cyber-Physical Production Systems (CPPS) are introduced as main actors of this manufact... Read More about Agent-based manufacturing — review and expert evaluation.

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.

Big Data Life Cycle in Shop-floor – Trends and Challenges (2023)
Journal Article
Pulikottil, T., Estrada-Jimenez, L. A., Abadia, J. J. P., Carrera-Rivera, A., Torayev, A., Rehman, H. U., …Barata, J. (2023). Big Data Life Cycle in Shop-floor – Trends and Challenges. IEEE Access, 11, 30008-30026. https://doi.org/10.1109/ACCESS.2023.3253286

Big data is defined as a large set of data that could be structured or unstructured. In manufacturing shop-floor, big data incorporates data collected at every stage of the production process. This includes data from machines, connecting devices, and... Read More about Big Data Life Cycle in Shop-floor – Trends and Challenges.

A maturity model for the autonomy of manufacturing systems (2023)
Journal Article
Mo, F., Monetti, F. M., Torayev, A., Rehman, H. U., Mulet Alberola, J. A., Rea Minango, N., …Chaplin, J. C. (2023). A maturity model for the autonomy of manufacturing systems. International Journal of Advanced Manufacturing Technology, 126(1-2), 405-428. https://doi.org/10.1007/s00170-023-10910-7

Modern manufacturing has to cope with dynamic and changing circumstances. Market fluctuations, the effects caused by unpredictable material shortages, highly variable product demand, and worker availability all require system robustness, flexibility,... Read More about A maturity model for the autonomy of manufacturing systems.

A framework for manufacturing system reconfiguration and optimisation utilising digital twins and modular artificial intelligence (2023)
Journal Article
Mo, F., Rehman, H. U., Monetti, F. M., Chaplin, J. C., Sanderson, D., Popov, A., …Ratchev, S. (2023). A framework for manufacturing system reconfiguration and optimisation utilising digital twins and modular artificial intelligence. Robotics and Computer-Integrated Manufacturing, 82, Article 102524. https://doi.org/10.1016/j.rcim.2022.102524

Digital twins and artificial intelligence have shown promise for improving the robustness, responsiveness, and productivity of industrial systems. However, traditional digital twin approaches are often only employed to augment single, static systems... Read More about A framework for manufacturing system reconfiguration and optimisation utilising digital twins and modular artificial intelligence.

Service Based Approach to Asset Administration Shell for Controlling Testing Processes in Manufacturing (2022)
Journal Article
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. IFAC-PapersOnLine, 55(10), 1852-1857. https://doi.org/10.1016/j.ifacol.2022.09.668

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.

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.