A knowledge-driven approach for process supervision in chemical plants

Autores
Musulin, Estanislao; Roda, Fernando
Año de publicación
2013
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In this work, an ontology-based framework for process supervision in chemical plants is presented. A conceptualization of equipment, control systems and hazards has been developed. This conceptual model includes the semantic of each modeled term in order to obtain a heavyweight ontology. The ontology has been formalized using Description Logic (DL). A knowledge-driven approach has been adopted in order to demonstrate how DL reasoning could be used to support process supervision, detecting and diagnosing faults, without the help of external agents. In the proposed approach, a DL reasoner adds implicit facts to the ontology through forward chaining reasoning, from the current measurements to the characterization of hazards. Additionally, the system is able to check knowledge consistency and formally explain the obtained results. The system functionality has been illustrated in the Tennessee Eastman process.benchmark.
Fil: Musulin, Estanislao. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - CONICET - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; Argentina
Fil: Roda, Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - CONICET - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; Argentina
Materia
ALARM MANAGEMENT
DESCRIPTION LOGIC
ONTOLOGY
PROCESS SUPERVISION
TENNESSEE EASTMAN PROCESS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/1439
Acceder
id CONICETDig_6ee6a89898e38c7d2b21e43d72242962
oai_identifier_str oai:ri.conicet.gov.ar:11336/1439
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling A knowledge-driven approach for process supervision in chemical plantsMusulin, EstanislaoRoda, FernandoALARM MANAGEMENTDESCRIPTION LOGICONTOLOGYPROCESS SUPERVISIONTENNESSEE EASTMAN PROCESShttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2https://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2In this work, an ontology-based framework for process supervision in chemical plants is presented. A conceptualization of equipment, control systems and hazards has been developed. This conceptual model includes the semantic of each modeled term in order to obtain a heavyweight ontology. The ontology has been formalized using Description Logic (DL). A knowledge-driven approach has been adopted in order to demonstrate how DL reasoning could be used to support process supervision, detecting and diagnosing faults, without the help of external agents. In the proposed approach, a DL reasoner adds implicit facts to the ontology through forward chaining reasoning, from the current measurements to the characterization of hazards. Additionally, the system is able to check knowledge consistency and formally explain the obtained results. The system functionality has been illustrated in the Tennessee Eastman process.benchmark.Fil: Musulin, Estanislao. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - CONICET - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; ArgentinaFil: Roda, Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - CONICET - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; ArgentinaPergamon-Elsevier Science Ltd2013-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/1439Musulin, Estanislao; Roda, Fernando; A knowledge-driven approach for process supervision in chemical plants; Pergamon-Elsevier Science Ltd; Computers and Chemical Engineering; 59; 6-2013; 164-1770098-1354enginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.compchemeng.2013.06.009info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T11:14:32Zoai:ri.conicet.gov.ar:11336/1439instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-22 11:14:32.828CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A knowledge-driven approach for process supervision in chemical plants
title A knowledge-driven approach for process supervision in chemical plants
spellingShingle A knowledge-driven approach for process supervision in chemical plants
Musulin, Estanislao
ALARM MANAGEMENT
DESCRIPTION LOGIC
ONTOLOGY
PROCESS SUPERVISION
TENNESSEE EASTMAN PROCESS
title_short A knowledge-driven approach for process supervision in chemical plants
title_full A knowledge-driven approach for process supervision in chemical plants
title_fullStr A knowledge-driven approach for process supervision in chemical plants
title_full_unstemmed A knowledge-driven approach for process supervision in chemical plants
title_sort A knowledge-driven approach for process supervision in chemical plants
dc.creator.none.fl_str_mv Musulin, Estanislao
Roda, Fernando
author Musulin, Estanislao
author_facet Musulin, Estanislao
Roda, Fernando
author_role author
author2 Roda, Fernando
author2_role author
dc.subject.none.fl_str_mv ALARM MANAGEMENT
DESCRIPTION LOGIC
ONTOLOGY
PROCESS SUPERVISION
TENNESSEE EASTMAN PROCESS
topic ALARM MANAGEMENT
DESCRIPTION LOGIC
ONTOLOGY
PROCESS SUPERVISION
TENNESSEE EASTMAN PROCESS
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
https://purl.org/becyt/ford/2.4
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv In this work, an ontology-based framework for process supervision in chemical plants is presented. A conceptualization of equipment, control systems and hazards has been developed. This conceptual model includes the semantic of each modeled term in order to obtain a heavyweight ontology. The ontology has been formalized using Description Logic (DL). A knowledge-driven approach has been adopted in order to demonstrate how DL reasoning could be used to support process supervision, detecting and diagnosing faults, without the help of external agents. In the proposed approach, a DL reasoner adds implicit facts to the ontology through forward chaining reasoning, from the current measurements to the characterization of hazards. Additionally, the system is able to check knowledge consistency and formally explain the obtained results. The system functionality has been illustrated in the Tennessee Eastman process.benchmark.
Fil: Musulin, Estanislao. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - CONICET - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; Argentina
Fil: Roda, Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - CONICET - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; Argentina
description In this work, an ontology-based framework for process supervision in chemical plants is presented. A conceptualization of equipment, control systems and hazards has been developed. This conceptual model includes the semantic of each modeled term in order to obtain a heavyweight ontology. The ontology has been formalized using Description Logic (DL). A knowledge-driven approach has been adopted in order to demonstrate how DL reasoning could be used to support process supervision, detecting and diagnosing faults, without the help of external agents. In the proposed approach, a DL reasoner adds implicit facts to the ontology through forward chaining reasoning, from the current measurements to the characterization of hazards. Additionally, the system is able to check knowledge consistency and formally explain the obtained results. The system functionality has been illustrated in the Tennessee Eastman process.benchmark.
publishDate 2013
dc.date.none.fl_str_mv 2013-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/1439
Musulin, Estanislao; Roda, Fernando; A knowledge-driven approach for process supervision in chemical plants; Pergamon-Elsevier Science Ltd; Computers and Chemical Engineering; 59; 6-2013; 164-177
0098-1354
url http://hdl.handle.net/11336/1439
identifier_str_mv Musulin, Estanislao; Roda, Fernando; A knowledge-driven approach for process supervision in chemical plants; Pergamon-Elsevier Science Ltd; Computers and Chemical Engineering; 59; 6-2013; 164-177
0098-1354
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.compchemeng.2013.06.009
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Pergamon-Elsevier Science Ltd
publisher.none.fl_str_mv Pergamon-Elsevier Science Ltd
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1846781567118082048
score 12.982451

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