Enhancing production system resilience with digital twin-driven management | ||
| dc.conicet.fuente | Crossref | |
| dc.conicet.organizacion | Universidad Nacional del Sur. Departamento de Ciencias de la Administración | |
| dc.conicet.organizacion | Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca | |
| dc.conicet.organizacion | Universidad Nacional del Sur. Departamento de Ingeniería | |
| dc.conicet.organizacion | Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca | |
| dc.conicet.paisOrganizacion | Argentina | |
| dc.conicet.paisOrganizacion | Argentina | |
| dc.conicet.paisOrganizacion | Argentina | |
| dc.conicet.paisOrganizacion | Argentina | |
| dc.conicet.produccionid | 12215120 | |
| dc.contributor.author | Sánchez, Marisa Analía | |
| dc.contributor.author | Rossit, Daniel Alejandro | |
| dc.contributor.author | Tohmé, Fernando Abel | |
| dc.date.accessioned | 2025-02-17T10:47:12Z | |
| dc.date.available | 2025-02-17T10:47:12Z | |
| dc.date.issued | 2024-11-21 | |
| dc.date.updated | 2024-12-26T12:21:37Z | |
| dc.description.abstract | In the last decade, significant advancements in digital technologies have revolutionized production systems, leading to the development of Cyber-Physical Systems (CPS) and Digital Twins (DT). This paper proposes a design of a production management system that leverages a Digital Twin associated with the shop floor. The objective is to enhance the resilience of production systems by providing real-time monitoring and enabling cloud-based outsourcing during production line failures. The methodology involves creating a Digital Twin model of the CPS, which is used to monitor the production process and visualize key performance indicators through a business intelligence tool. The contribution of this study lies in addressing the growing need for resilient production systems capable of withstanding disruptions and unexpected events. The DT provides accurate information useful for making informed decisions during disruptions. This research contributes to improving management practices by integrating production and enterprise data, facilitating decision-making processes aligned with company objectives, and enhancing the overall resilience of production systems. These findings illustrate the potential of cloud production services to maintain service levels. Among the academic contributions of this paper, is the use of System Dynamics as a suitable approach to modeling the behavior of a digital twin. | es |
| dc.description.fil | Fil: Sánchez, Marisa Analía. Universidad Nacional del Sur. Departamento de Ciencias de la Administración; Argentina | |
| dc.description.fil | Fil: Rossit, Daniel Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina | |
| dc.description.fil | Fil: Tohmé, Fernando Abel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina | |
| dc.format | application/pdf | es |
| dc.identifier.citation | Sánchez, Marisa Analía; Rossit, Daniel Alejandro; Tohmé, Fernando Abel; Enhancing production system resilience with digital twin-driven management; Taylor & Francis Ltd; International Journal Of Computer Integrated Manufacturing; 21-11-2024; 1-20 | es |
| dc.identifier.institucional | CONICET | |
| dc.identifier.issn | 0951-192X | es |
| dc.identifier.repo | CONICET Digital | |
| dc.identifier.uri | http://hdl.handle.net/11336/254551 | |
| dc.journal.ciudad | Londres | es |
| dc.journal.pagination | 1-20 | es |
| dc.journal.pais | Reino Unido | es |
| dc.journal.title | International Journal Of Computer Integrated Manufacturing | es |
| dc.language.iso | eng | es |
| dc.publisher | Taylor & Francis Ltd | es |
| dc.relation.alternativeid | info:eu-repo/semantics/altIdentifier/url/https://www.tandfonline.com/doi/full/10.1080/0951192X.2024.2428686 | |
| dc.relation.alternativeid | info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1080/0951192X.2024.2428686 | |
| dc.rights | info:eu-repo/semantics/restrictedAccess | * |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ | * |
| dc.subject | DIGITAL TWIN | es |
| dc.subject | RESILIENCE | es |
| dc.subject | CYBER-PHYSICAL SYSTEMS | es |
| dc.subject | INDUSTRY 4.0 | es |
| dc.subject | SMART MANUFACTURING | es |
| dc.subject.classification | Otras Ingenierías y Tecnologías | es |
| dc.subject.classification | Otras Ingenierías y Tecnologías | es |
| dc.subject.classification | INGENIERÍAS Y TECNOLOGÍAS | es |
| dc.title | Enhancing production system resilience with digital twin-driven management | es |
| dc.type | info:eu-repo/semantics/article | |
| dc.type | info:ar-repo/semantics/artículo | |
| dc.type | info:eu-repo/semantics/publishedVersion | |
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