Mrs GIOVANNA MARTINEZ ARELLANO's Outputs (32)

A Tool for Generating and Labelling Domain Randomised Synthetic Images for Object Recognition in Manufacturing (2024)
Presentation / Conference Contribution
Martínez-Arellano, G., & Buck, M. G. (2024, October). A Tool for Generating and Labelling Domain Randomised Synthetic Images for Object Recognition in Manufacturing. Paper presented at ESAIM 2024 – 2nd European Symposium on Artificial Intelligence in Manufacturing, Athens. Greece

Reconfigurable manufacturing systems are becoming the only viable option to respond to changing product volumes and product specification , which are currently major challenges for the manufacturing industry. Part of this adaptation requires vision s... Read More about A Tool for Generating and Labelling Domain Randomised Synthetic Images for Object Recognition in Manufacturing.

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.

Towards Frugal Industrial AI: a framework for the development of scalable and robust machine learning models in the shop floor (2024)
Journal Article
Martínez-Arellano, G., & Ratchev, S. (2024). Towards Frugal Industrial AI: a framework for the development of scalable and robust machine learning models in the shop floor. International Journal of Advanced Manufacturing Technology, https://doi.org/10.1007/s00170-024-14508-5

Artificial intelligence (AI) among other digital technologies promise to deliver the next level of process efficiency of manufacturing systems. Although these solutions such as machine learning (ML) based condition monitoring and quality inspection a... Read More about Towards Frugal Industrial AI: a framework for the development of scalable and robust machine learning models in the shop floor.

AdaptUI: A Framework for the development of Adaptive User Interfaces in Smart Product-Service Systems (2024)
Journal Article
Carrera-Rivera, A., Larrinaga, F., Lasa, G., Martinez-Arellano, G., & Unamuno, G. (2024). AdaptUI: A Framework for the development of Adaptive User Interfaces in Smart Product-Service Systems. User Modeling and User-Adapted Interaction, https://doi.org/10.1007/s11257-024-09414-0

Smart Product–Service Systems (S-PSS) represent an innovative business model that integrates intelligent products with advanced digital capabilities and corresponding e-services. The user experience (UX) within an S-PSS is heavily influenced by the c... Read More about AdaptUI: A Framework for the development of Adaptive User Interfaces in Smart Product-Service Systems.

Improving the Development and Reusability of Industrial AI Through Semantic Models (2024)
Presentation / Conference Contribution
Martínez-Arellano, G., & Ratchev, S. (2024, April). Improving the Development and Reusability of Industrial AI Through Semantic Models. Presented at Conference on Learning Factories 2024, University of Twente, The Netherlands

Despite some of the success of AI, particularly machine learning, in industrial applications such as condition monitoring, quality inspection and asset control , solutions are typically bespoke and not robust in the long term. There is a considerable... Read More about Improving the Development and Reusability of Industrial AI Through Semantic Models.

Towards Frugal Industrial AI : A Framework for the Development of Scalable and Robust Machine Learning Models in the Shop Floor (2024)
Presentation / Conference Contribution
MARTINEZ ARELLANO, G. (2024, June). Towards Frugal Industrial AI : A Framework for the Development of Scalable and Robust Machine Learning Models in the Shop Floor. Paper presented at FAIM 2024, Taichung, Taiwan

Artificial Intelligence (AI) among other digital technologies promise to deliver the next level of process efficiency of manufacturing systems. Although these solutions such as machine learning (ML) based condition monitoring and quality inspection a... Read More about Towards Frugal Industrial AI : A Framework for the Development of Scalable and Robust Machine Learning Models in the Shop Floor.

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.

Immune system inspired smart maintenance framework: tool wear monitoring use case (2024)
Journal Article
Pulikottil, T., Martínez-Arellano, G., & Barata, J. (2024). Immune system inspired smart maintenance framework: tool wear monitoring use case. International Journal of Advanced Manufacturing Technology, 132(9-10), 4699-4721. https://doi.org/10.1007/s00170-024-13472-4

As the manufacturing industry is moving towards the fourth industrial revolution, there is an increasing need for smart maintenance systems that could provide manufacturers with a competitive advantage by predicting failures. Despite various efforts... Read More about Immune system inspired smart maintenance framework: tool wear monitoring use case.

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.

Investigating multi-level ontology to support manufacturing during demand fluctuation (2023)
Presentation / Conference Contribution
Kazantsev, N., Niewiadomski, K., Martínez-Arellano, G., Elshafei, B., Mo, F., & Murthy, S. R. (2023, September). Investigating multi-level ontology to support manufacturing during demand fluctuation. Presented at Low-Cost Digital Solutions for Industrial Automation (LoDiSA 2023), Cambridge, UK

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.

Classification of cancer cells at the sub-cellular level by phonon microscopy using deep learning (2023)
Journal Article
Pérez-Cota, F., Martínez-Arellano, G., La Cavera III, S., Hardiman, W., Thornton, L., Fuentes-Domínguez, R., Smith, R. J., McIntyre, A., & Clark, M. (2023). Classification of cancer cells at the sub-cellular level by phonon microscopy using deep learning. Scientific Reports, 13, Article 16228. https://doi.org/10.1038/s41598-023-42793-9

There is a consensus about the strong correlation between the elasticity of cells and tissue and their normal, dysplastic, and cancerous states. However, developments in cell mechanics have not seen significant progress in clinical applications. In t... Read More about Classification of cancer cells at the sub-cellular level by phonon microscopy using deep learning.

Methodology for Digital Transformation: A Continuous Improvement Approach (2023)
Presentation / Conference Contribution
Hernández Oliver, K., Martínez-Arellano, G., & Segal, J. (2023, September). Methodology for Digital Transformation: A Continuous Improvement Approach. Presented at 1st Workshop on Low-Cost Digital Solutions for Industrial Automation, Cambridge, UK

Digital technologies have the potential to significantly transform the manufacturing industry by achieving improvements in productivity, quality and sustainability. Despite this, the uptake is relatively low as companies face a number of challenges i... Read More about Methodology for Digital Transformation: A Continuous Improvement Approach.

Low-cost System for Visual Inspection of Corrosion: An Industrial Case Study (2023)
Presentation / Conference Contribution
Hernández Oliver, K. H., Martínez-Arellano, G., & Segal, J. (2023, September). Low-cost System for Visual Inspection of Corrosion: An Industrial Case Study. Presented at 1st Workshop on Low-Cost Digital Solutions for Industrial Automation, Cambridge, UK

The use of digital technologies around the world has increased considerably, modifying the way in which daily activities are conducted. The manufacturing sector is no exception. Over the last decade, digital technologies have become a key element for... Read More about Low-cost System for Visual Inspection of Corrosion: An Industrial Case Study.

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.

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.

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.

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)
Presentation / Conference Contribution
Elshafei, B., Mo, F., Chaplin, J. C., Arellano, G. M., & Ratchev, S. Capacity Modelling and Measurement for Smart Elastic Manufacturing Systems. Presented at Aerotech 2023, Fort Worth, Texas, USA

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.

UX- for Smart-PSS: Towards a Context-aware Framework (2022)
Presentation / Conference Contribution
Carrera-Rivera, A., Larrinaga, F., Lasa, G., & Martinez-Arellano, G. (2022, October). UX- for Smart-PSS: Towards a Context-aware Framework. Presented at 6th International Conference on Computer-Human Interaction Research and Applications (CHIRA 2022), Valletta, Malta