Skip to main content

Research Repository

Advanced Search

All Outputs (29)

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.

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). 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.

Capacity Modelling and Measurement for Smart Elastic Manufacturing Systems (2023)
Presentation / Conference Contribution
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.

Self-configuration of a Robotic Platform to support a self-organized Manufacturing Process (2022)
Presentation / Conference Contribution
Jimenez, L. A. E., Sanderson, D., Chaplin, J. C., & Barata, J. (2022). Self-configuration of a Robotic Platform to support a self-organized Manufacturing Process. In IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society. https://doi.org/10.1109/IECON49645.2022.9968868

Self-configuration in manufacturing is a key trend to generate adaptable production systems. Different product requirements need different machine settings and continuous software update. Existing approaches usually assume that manufacturing resource... Read More about Self-configuration of a Robotic Platform to support a self-organized Manufacturing Process.

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)
Presentation / Conference Contribution
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)
Presentation / Conference Contribution
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.

Application of Multi Agent Systems for Leak Testing (2021)
Presentation / Conference Contribution
Rehman, H. U., Chaplin, J. C., Zarzycki, L., Jones, M., & Ratchev, S. (2021). Application of Multi Agent Systems for Leak Testing. . https://doi.org/10.1109/ICSC50472.2021.9666580

The manufacturing of customised products is a driver in the trend of incorporating intelligence in the system. This intelligence is required to enable the system to self-conFigure processes to meet the requirements of unique products. This work deals... Read More about Application of Multi Agent Systems for Leak Testing.

Visualisation on a Shoestring: a low-cost approach for building visualisation components of industrial digital solutions (2021)
Presentation / Conference Contribution
Martínez-Arellano, G., McNally, M. J., Chaplin, J. C., Ling, Z., McFarlane, D., & Ratchev, S. (2021). Visualisation on a Shoestring: a low-cost approach for building visualisation components of industrial digital solutions. In Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future : Proceedings of SOHOMA’21

The rate of adoption of digital solutions in manufacturing environments remains low despite the benefits these can bring. This is particularly acute among industrial small and medium enterprises (SMEs), who typically do not have the confidence to ado... Read More about Visualisation on a Shoestring: a low-cost approach for building visualisation components of industrial digital solutions.

Cloud Based Decision Making for Multi-Agent Production Systems (2021)
Presentation / Conference Contribution
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.

A Framework for Self-Configuration in Manufacturing Production Systems (2021)
Presentation / Conference Contribution
Rehman, H. U., Chaplin, J. C., Zarzycki, L., & Ratchev, S. (2021). A Framework for Self-Configuration in Manufacturing Production Systems. . https://doi.org/10.1007/978-3-030-78288-7_7

Intelligence in manufacturing enables the optimization and configuration of processes, and a goal of future smart manufacturing is to enable processes to configure themselves-called self-configuration. This paper describes a framework for utilising d... Read More about A Framework for Self-Configuration in Manufacturing Production Systems.

Industrial Robots 4.0 (2020)
Book Chapter
Fassi, I., Pio Negri, S., Pagano, C., Rebaioli, L., & Valori, M. (2020). Industrial Robots 4.0. In J. Chaplin, C. Pagano, & S. Fort (Eds.), Digital Manufacturing for SMEs: An Introduction (191-212). Digit-T. https://doi.org/10.17639/vjvt-7681