Brief description of the paper/report. Identification

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1 Brief description of the paper/report Argument Original reference A holonic framework for coordination and optimization in oil and gas production complexes E. Chacon, I. Besembel, Univ. Los Andes, Mérida, Venezuela, J.- C. Hennet, LAAS-CNRS, Toulouse, France Coordination and optimization in oil and gas production complexes. Computers in Industry 53 (2004) Identification Keywords issues Products Sector Terms of process English National language (French) software & application Logiciels & applications Information & description Information & description method Méthodologie Objects & systems Objets & systèmes automotive Automobile Plastics Plastiques chemistry Chimie Food & beverage Aliments et boissons Pharmaceutical Pharmacie aerospace Aérospatial Financial Finance Services Services advertisement & media Publicité et Media nature & environment Nature & environnement architecture Architecture biology Biologie electronic & computer Electronique et ordinateurs education & science Education et science authorities & federations Administrations et fédérations engineering Ingénierie manufacturing Production manufacturière Research & development Recherche et développement service Service marketing Commercialisation production Production design Conception

2 Operation Structure (OS) Organization Arrangement (OA) Interactions with Socio-Economic Environment (ISEE) Abstract controlling Control cooperation Coopération communication Communication coordination Coordination distribution of production operations & volumes employment of different skills optimizing of logistic transport capacities over internal links communication of management responsibilities and information negotiation of internal agreements/ control mechanisms, or agreements with external bodies selecting of assure best efficiency/ effectiveness of organization chart or coordination strategy negotiation of commercial agreements with client/supplier for max profit for the network deciding of a network innovation program by the partners and negotiated with financiers forecasting of dynamic evolution of a network In continuous production networks such as oil fields, global optimization requires to optimize not only production mechanisms, but also scheduling mechanisms for continuous flows of products through the different units that belong to the production complex. Two functions must be performed in order to efficiently operate a production network: coordination to ensure coherence and consistency of states, controls and decisions; and selection of the best configuration and set-points to run the process according to optimization criteria. The hybrid nature of this problem stems from the continuous processes involved and the use of discrete decision mechanisms to supervise the global behavior of the production process. To increase reactivity and reduce complexity in the global control scheme, each component of the system is described as a holon and the complex forms a holarchy. Each holon interacts with the other holons to contribute to the system s optimization. Interaction is based on negotiation processes performed by agents that represent each holon. x x Répartition des opérations et des volumes de production Emploi de différentes compétences Optimisation des capacités de transport en logistique interne Diffusion des directives de gestion et des informations Négociation d accords internes, de mécanismes de contrôle ou d accords avec des entités externes Sélection de schémas d organisation ou de stratégies de coordination assurant la meilleure efficience/efficacité Négociation d accords commerciaux avec les clients/fournisseurs pour maximiser le profit du réseau Choix par les partenaires d un programme d innovation pour le réseau, négocié avec les financiers Prévision de l évolution dynamique d un réseau mechanism and at which layer) could be more effective in reducing the variability amplification. Description

3 English National language Description of the problem approached Results The study considers large production networks with the application case of an oil field. Production is continuous and geographically distributed. Its coordination and optimization requires to consider several decisional levels and a distributed control structure. Two functions must be performed in order to efficiently operate a production network: coordination to ensure coherence and consistency of states, controls and decisions; and selection of the best configuration and set-points to run the process according to optimization criteria. The hybrid nature of this problem stems from the continuous processes involved and the use of discrete decision mechanisms to supervise the global behavior of the production process. To increase reactivity and reduce complexity in the global control scheme, each component of the system is described as a holon and the complex forms a holarchy. Each holon interacts with the other holons to contribute to the system s optimization. Interaction is based on negotiation processes performed by agents that represent each holon. The paper proposes different views of the production network, with their corresponding models: a static view, represented by a UML graph of classes, a hybrid structure for decision and control at each Production Unit, a behavioral description of a production unit, modeled by a Petri net. The control and decision layers for each holonic production unit are split into two components: physical process, decision and information. They define a set of hybrid systems interconnected by product flows at the physical level and by information flows at the decisional level. Decisions are taken at the local level by intelligent agents able to negotiate decisions and implement them. The global coordination of the production network is viewed as a supervision level for the integrated system.

4 Information for the End Users and Links What s new? What s useful? Tools (technologies) for the implementation of results. Links to the Main CODESNET Issues Additional Remarks In the proposed scheme, tactical and operational decisions are treated at the level of production units. The central decision making process sets production goals which are evaluated and performed if possible after negotiation at the local level. The models presented show how to combine different views of the system: holonic view of Production Units, logical interactions, distributed decision structure, hybrid control system. The proposed control structure has the advantage of simplicity at the central level and reactivity at the local level. Evaluation of production units is made easy, both in the decision layer and in the physical layer. The proposed coordination structure and tools rely on : a modern information and communication network a distributed multi-agent platform Local Production Unit Architectures (PUA) that achieve: o control of the physical process o updating of state variables o exchange of information with the supervisor o negotiation with other PU To be compiled by the CODESNET partners Suggestions by the author(s) are welcome (please look at the Library input page for the list of 9 issues) The general decision and control scheme is appealing. It was designed for the Maracaibo oil field, in Venezuela. Unfortunately, it has not been implemented yet because of organizational changes in the Venezuelian oil industry.

5 Conceptual scheme of the paper contents: Sequence diagram for PUA negotiation

6 IT Architecture to implement the system