Enhancing Supply Chain Efficiency Through Manufacturing Optimisation as a Service (MOaaS)
[EN] Modern supply chains, particularly for small- and medium-sized enterprises (SMEs), face significant challenges due to globalisation, technological evolution and dynamic market demands. Traditional supply chain management (SCM) systems often fall short in addressing these complexities, especiall...
| Autores: | , , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:dnet:riunet______::f93daf58863578f64072eb8a7f606f0d |
| Acceso en línea: | https://riunet.upv.es/handle/10251/234697 |
| Access Level: | acceso embargado |
| Palabra clave: | Supply chain Cloud Manufacturing Machine Learning 08.- Fomentar el crecimiento económico sostenido, inclusivo y sostenible, el empleo pleno y productivo, y el trabajo decente para todos 09.- Desarrollar infraestructuras resilientes, promover la industrialización inclusiva y sostenible, y fomentar la innovación |
| Sumario: | [EN] Modern supply chains, particularly for small- and medium-sized enterprises (SMEs), face significant challenges due to globalisation, technological evolution and dynamic market demands. Traditional supply chain management (SCM) systems often fall short in addressing these complexities, especially for SMEs constrained by technological limitations, resource shortages and external pressures. This paper describes C2NET, a cloud-based platform that introduces manufacturing optimisation as a service (MOaaS), which provides businesses with access to advanced optimisation techniques without the need for extensive in-house infrastructure. By leveraging cloud computing, machine learning and collaborative frameworks, C2NET delivers scalable, cost-effective and sector-specific optimisation solutions. Through practical case studies, C2NET demonstrates significant solution development improvements. This work advances the C2NET platform by integrating machine learning-driven optimisation and auto-scaling cloud infrastructures, and by addressing gaps in prior studies that focus solely on algorithmic frameworks. Future implementations aim to integrate simulation tools, advanced machine learning techniques and predictive analytics to further solidify C2NET¿s role as a transformative tool in modern supply chain optimisation. This approach eliminates the need for costly infrastructure investments and specialised information and technology (IT) expertise, which makes advanced optimisation accessible to a broader range of businesses, particularly SMEs. |
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