Publicación: Enhancing consistency in piping and instrumentation diagrams using DistilBERT and smart PID systems
| dc.contributor.author | Gómez-Vega, F.S. | |
| dc.contributor.author | Acuña, O. | |
| dc.contributor.author | Camargo, Andrea C. | |
| dc.contributor.author | Jimenez, Jeison D. | |
| dc.contributor.author | Galeano, Sara M. | |
| dc.contributor.author | Franco, Isabella E. | |
| dc.contributor.author | Lozano, Laura L. | |
| dc.contributor.author | Vásquez Aguilar, Jenifer Yoris | |
| dc.contributor.author | Puertas Del Castillo, Edwin Alexander | |
| dc.contributor.researchgroup | Grupo de Investigación Tecnologías Aplicadas y Sistemas de Información (GRITAS) | |
| dc.contributor.seedbeds | Semillero de Investigación en Inteligencia Artificial | |
| dc.date.accessioned | 2025-08-28T13:40:47Z | |
| dc.date.issued | 2025-08-09 | |
| dc.description | Contiene gráficos | |
| dc.description.abstract | This study presents a novel approach utilizing DistilBERT, a lightweight variant of BERT, to identify inconsistencies in piping and instrumentation diagrams (P&IDs) within SmartPID systems. A structured dataset was constructed by extracting engineering design data from a SQL-based SmartPID database, monitoring all modifications and updates made throughout the design phase. The DistilBERT model was fine-tuned on this dataset to recognize inconsistencies in real-time, achieving an impressive F1 score of 99% and a loss of 0.04%. The model’s performance was validated by domain experts, who confirmed the detected inconsistencies as highly accurate. Our approach significantly reduces the manual effort required for P&ID review and improves design consistency, demonstrating the potential for enhanced safety and efficiency in complex industrial projects. Future work will focus on refining the model’s parameters and expanding its application across different industries. | eng |
| dc.description.researcharea | Inteligencia artificial | |
| dc.description.researcharea | Analítica de datos y Big Data | |
| dc.format.extent | 9 páginas | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.citation | Gómez-Vega, F. S., Acuña, O., Camargo, A. C., Jimenez, J. D., Galeano, S. M., Franco, I. E., ... & Puertas, E. (2025). Enhancing consistency in piping and instrumentation diagrams using DistilBERT and smart PID systems. Systems and Soft Computing, 200373. | |
| dc.identifier.doi | https://doi.org/10.1016/j.sasc.2025.200373 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12585/14179 | |
| dc.language.iso | eng | |
| dc.publisher | Systems and Soft Computing | |
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| dc.rights.license | Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0) | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject.proposal | Databases | |
| dc.subject.proposal | P&ID | |
| dc.subject.proposal | Consistency | |
| dc.subject.proposal | DistilBERT | |
| dc.subject.proposal | Machine learning | |
| dc.subject.proposal | Design software | |
| dc.title | Enhancing consistency in piping and instrumentation diagrams using DistilBERT and smart PID systems | eng |
| dc.type | Artículo de revista | |
| dc.type.coar | http://purl.org/coar/resource_type/c_18cf | |
| dc.type.coarversion | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |
| dc.type.content | Text | |
| dc.type.driver | info:eu-repo/semantics/article | |
| dc.type.redcol | http://purl.org/redcol/resource_type/ART | |
| dc.type.version | info:eu-repo/semantics/publishedVersion | |
| dcterms.audience | Research | eng |
| dspace.entity.type | Publication | |
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