CHEM: Advanced decision support systems for chemical/petrochemical process industries

Cauvin, Sylvie; Celse, Benoit

doi:10.1016/s1570-7946(04)80237-2

Cited by 9 publications

(10 citation statements)

References 6 publications

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“…"The aim of the CHEM-DSS project is to develop and implement an advanced Decision Support System (DSS) for process monitoring, data and event analysis, and operation support in industrial processes, mainly in refining, chemical and petrochemical processes" (Cauvin, 2004b). The CHEM-DSS research project was initiated to compete and build on the two main initiatives in the United States, namely, the Abnormal Situation Management (ASM) Consortium led by Honeywell, and the Intelligent Control Program of NIST.…”

Section: Advanced Decision Support System For Chemical/petrochemical mentioning

confidence: 99%

“…The industrial end-users provided different kinds of processes including a fluid catalytic cracking pilot plant, a paper making process, a gasifier pilot plant, a steam generator, a blast furnace and distillation process. End users can use the developed toolboxes to design their own intelligent diagnostic system according to their requirements" (Cauvin, 2004a). …”

Section: Advanced Decision Support System For Chemical/petrochemical mentioning

confidence: 99%

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Multi-agent Systems for Industrial Applications: Design, Development, and Challenges

Sayda¹

2011

Multi-Agent Systems - Modeling, Control, Programming, Simulations and Applications

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Section: Advanced Decision Support System For Chemical/petrochemical mentioning

confidence: 99%

Section: Advanced Decision Support System For Chemical/petrochemical mentioning

confidence: 99%

Multi-agent Systems for Industrial Applications: Design, Development, and Challenges

Sayda¹

2011

Multi-Agent Systems - Modeling, Control, Programming, Simulations and Applications

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“…The ontology described in the previous section has been created using the tool Protegé 2000 (Noy et al, 2003) with the purpose of integrating different supervision, fault detection and diagnosis toolboxes, within the context of the CHEM project (Cauvin, 2002). These toolboxes are the result of encapsulating SFDD techniques which provide a common description and interface for users.…”

Section: Ontology For Sfddmentioning

confidence: 99%

“…Our goal here is to develop an ontology that provides semantic interoperability. In particular, we focus on integrating heterogeneous tools for supervision, fault detection and diagnosis (SFDD) within the context of the CHEM European project (Cauvin, 2002). This paper is organized as follows: First, in section 2 we explain what holonic multi-agent systems are and in section 3 we make some ontology definitions.…”

Section: Introductionmentioning

confidence: 99%

Ontology for Integrating Heterogeneous Tools for Supervision, Fault Detection and Diagnosis

López

Meléndez

Suárez³

2005

Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics

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Abstract:The Distributed Supervision Systems that have been used extensively for the last fifteen years in the process industry are now evolving towards higher level solutions based on better connections between applications and processes that assure that data flows from the process to manage boards. Knowledge sharing seems to be a key issue in integrating these heterogeneous systems. In this paper we present an ontology as a first step to achieving semantic interoperability. The ontology has been conceived within the context of a complex integration problem, in which heterogeneous toolboxes cooperate to deal with several supervision, fault detection and diagnostic tasks for chemical processes. Regarding the current trends in ontology research, our proposal is consistent with top-level ontologies, as these kinds of ontologies seem to overcome the ontology integration problem. We describe a preliminary version of the ontology. The conceptualisation of control variables, system behaviour, supervision tasks, models and system properties is given. All attributes and relationships between each concept has been deployed. The ontology has been developed using Protete2000.

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“…Our method uses four successive complementary techniques Celse, 2004a, Cauvin andCelse, 2004b). They enable to go step by step from the observations to a sentence in natural language describing the faults: -Modelling: A quantitative causal model is elaborated from a dynamic behavioural model of the process.…”

Section: Introductionmentioning

confidence: 99%

Model Based Diagnostic Module for a FCC Pilot Plant

Celse

Cauvin

Heim

et al. 2005

Oil & Gas Science and Technology - Rev. IFP

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Résumé -Système de diagnostic d'un pilote de FCC à base de modèles -Cet article présente le système de diagnostic ASCO (Aide à la supervision et à la conduite des opérateurs) développé par l'IFP et testé hors ligne sur un pilote de FCC (Fluid Catalytic Cracking). Il fait successivement appel à quatre modules complémentaires. Ces derniers permettent, à partir d'un ensemble d'informations, de fournir aux opérateurs un message indiquant la panne et ses conséquences. Le premier module permet de générer un modèle causal quantitatif de bon fonctionnement du procédé. Le second module effectue la détection de défauts : il déclenche des alarmes à partir des observations. Ces alarmes sont ensuite traitées par le module de localisation (algorithme de hitting set) qui élabore une liste de composants physiques suspectés défaillants. Enfin, la connaissance des experts sur ces composants est traitée automatiquement par le module d'identification qui renvoie un message à l'opérateur. Ce message décrit la défaillance, les actions à entreprendre pour traiter l'opération ou pour la maintenance à effectuer, et les répercussions de la défaillance sur le procédé. Les résultats obtenus sont illustrés par quatre scénarios réels de mauvais comportement. Ce travail a été mené dans le cadre du projet européen CHEM. Abstract -Model Based Diagnostic Module for a FCC Pilot Plant -This paper presents a diagnostic module developed by IFP and tested off-line on a FCC (Fluid Catalytic

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CHEM: Advanced decision support systems for chemical/petrochemical process industries

Cited by 9 publications

References 6 publications

Multi-agent Systems for Industrial Applications: Design, Development, and Challenges

Multi-agent Systems for Industrial Applications: Design, Development, and Challenges

Ontology for Integrating Heterogeneous Tools for Supervision, Fault Detection and Diagnosis

Model Based Diagnostic Module for a FCC Pilot Plant

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