Outputs (41)

Semantic Modelling of a Manufacturing Value Chain: Disruption Response Planning (2024)
Journal Article
Elshafei, B., Martínez-Arellano, G., Chaplin, J. C., & Ratchev, S. (2024). Semantic Modelling of a Manufacturing Value Chain: Disruption Response Planning. IFAC-PapersOnLine, 58(19), 789-794. https://doi.org/10.1016/j.ifacol.2024.09.202

Supply chains have been profoundly impacted by recent global disruptions, resulting in widespread shortages of parts, goods, and raw materials, significantly affecting the manufacturing sector to the extent of halting production lin... Read More about Semantic Modelling of a Manufacturing Value Chain: Disruption Response Planning.

Semantic Knowledge Representation in Asset Administration Shells: Empowering Manufacturing Utilization (2024)
Presentation / Conference Contribution
Elshafei, B., Martínez-Arellano, G., Chaplin, J. C., Sanderson, D., & Ratchev, S. (2024, June). Semantic Knowledge Representation in Asset Administration Shells: Empowering Manufacturing Utilization. Paper presented at 33rd International Conference on Flexible Automation and Intelligent Manufacturing (FAIM 2024), Taiwan, Taichung

Within the context of Industry 4.0 and the Reference Architecture Model Industrie 4.0, the Asset Administration Shell (AAS) framework has emerged as a critical component for implementing Digital Twins that facilitate a seamless data exchange within a... Read More about Semantic Knowledge Representation in Asset Administration Shells: Empowering Manufacturing Utilization.

Optimal Manufacturing Configuration Selection: Sequential Decision Making and Optimization using Reinforcement Learning (2023)
Presentation / Conference Contribution
Torayev, A., Abadia, J. J. P., Martínez-Arellano, G., Cuesta, M., Chaplin, J. C., Larrinaga, F., Sanderson, D., Arrazola, P. J., & Ratchev, S. (2023, October). Optimal Manufacturing Configuration Selection: Sequential Decision Making and Optimization using Reinforcement Learning. Presented at 56th CIRP Conference onManufacturing Systems, CIRP CMS ‘23, Cape Town

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.

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.

Enabling Coordinated Elastic Responses of Manufacturing Systems through Semantic Modelling (2023)
Presentation / Conference Contribution
Martínez-Arellano, G., Niewiadomski, K., Mo, F., Elshafei, B., Chaplin, J. C., Mcfarlane, D., & Ratchev, S. (2023, July). Enabling Coordinated Elastic Responses of Manufacturing Systems through Semantic Modelling. Presented at IFAC World Congress 2023: The 22nd World Congress of the International Federation of Automatic Control, Yokohama, Japan

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.

Efficient decision-making in SMEs: leveraging knowledge graphs with Neo4j and AI vision (2023)
Presentation / Conference Contribution
Mo, F., Ur Rehman, H. U., Elshafei, B., Chaplin, J. C., Sanderson, D., Martínez-Arellano, G., & Ratchev, S. (2023, September). Efficient decision-making in SMEs: leveraging knowledge graphs with Neo4j and AI vision. Presented at Low-Cost Digital Solutions for Industrial Automation (LoDiSA 2023), Cambridge, UK

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., Sanderson, D., & 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.

Optimal Selection of Manufacturing Configurations Using Object-Oriented and Mathematical Data Models (2023)
Book Chapter
Torayev, A., Wang, Z., Martínez-Arellano, G., Chaplin, J. C., Sanderson, D., & Ratchev, S. (2023). Optimal Selection of Manufacturing Configurations Using Object-Oriented and Mathematical Data Models. In L.-C. Tang (Ed.), Industrial Engineering and Applications (3-12). IOS Press. https://doi.org/10.3233/ATDE230025

In this work, we optimize manufacturing configurations, i.e., the set of necessary assets, using the known capabilities and capacities of manufacturing equipment. In particular, the work provides an Object-Oriented data model and the translation of t... Read More about Optimal Selection of Manufacturing Configurations Using Object-Oriented and Mathematical Data Models.

Elastic manufacturing systems: A system view on operations, firm, and supply chain resilience (2023)
Presentation / Conference Contribution
Kazantsev, N., Niewiadomski, K., El-Shafei, B., Murthy, S. R., Chaplin, J., Martínez-Arellano, G., Ratchev, S., Velu, C., Mcfarlane, D., & Minshall, T. (2023, July). Elastic manufacturing systems: A system view on operations, firm, and supply chain resilience. Presented at 30th EurOMA Conference, Leuven, Belgium

'Black swan' events-such as military conflicts, pandemics, and semiconductor crises-drastically change product volume and mix patterns and shorten how long manufacturers have to cost-effectively respond to them. This is a particular challenge for hig... Read More about Elastic manufacturing systems: A system view on operations, firm, and supply chain resilience.