All Outputs (13)

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.

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.

Deep Dynamic Layout Optimisation of Photogrammetry Camera Position based on Digital Twin (2023)
Journal Article
Wang, L., Wang, Z., Kendall, P., Gumma, K., Turner, A., & Ratchev, S. (2023). Deep Dynamic Layout Optimisation of Photogrammetry Camera Position based on Digital Twin. IEEE Transactions on Automation Science and Engineering, https://doi.org/10.1109/TASE.2023.3323088

The photogrammetry system has been widely used in industrial manufacturing applications, such as high-precision assembly, reverse engineering and additive manufacturing. In order to meet the demand of the product variety and short product lifecycle,... Read More about Deep Dynamic Layout Optimisation of Photogrammetry Camera Position based on Digital Twin.

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.

Digital-twin deep dynamic camera position optimisation for the V-STARS photogrammetry system based on 3D reconstruction (2023)
Journal Article
Wang, L., Wang, Z., Kendall, P., Gumma, K., Turner, A., & Ratchev, S. (in press). Digital-twin deep dynamic camera position optimisation for the V-STARS photogrammetry system based on 3D reconstruction. International Journal of Production Research, 1-20. https://doi.org/10.1080/00207543.2023.2252108

Photogrammetry systems are widely used in industrial manufacturing applications as an assistance measurement tool. Not only does it provide high-precision feedback for assembly process inspection and product quality assessment, but also it can improv... Read More about Digital-twin deep dynamic camera position optimisation for the V-STARS photogrammetry system based on 3D reconstruction.

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.

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. 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.

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.

Elastic manufacturing systems: A system view on operations, firm, and supply chain resilience (2023)
Conference Proceeding
Kazantsev, N., Niewiadomski, K., El-Shafei, B., Murthy, S. R., Chaplin, J., Martínez-Arellano, G., …Minshall, T. (2023). Elastic manufacturing systems: A system view on operations, firm, and supply chain resilience.

'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.

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 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.