Abstract— Template for Modelling Refinery Logistics and Operation Using ARENA

Abstract—This work describes the development of a template of components for building discrete event simulation models of Petroleum Refinery Processes and Logistics. These components were conceived to be reusable, friendly editable, using industry specific units and terms, intuitive to the final user, and representing real world objects and procedures. The template was created using the software ARENA, combining continuous and discrete simulation components. Using this template we have built a simulation model of the logistics of the San Lorenzo refinery of PETROBRAS ENERGIA (Argentina). By using this tool, it was possible for analysts to evaluate the impact of new investments, testing different plant configurations, operational schemes, and demand scenarios. After testing the Template in this real case, we have obtained a valid, and reusable tool. Further applications of this tools might be in the field of refinery plant design. Also, this tool might be extensible to other process industries, using liquids, like: oil, milk, beverage, etc.Index Terms—Discrete event Simulation, Fluid flow,Petroleum, Software reusability.I NTRODUCTIONTraditionally, discrete event simulation has been applied extensively to represent discrete manufacturing processes, like automotive, steel, etc. In such models, “entities” represent parts moving in a system. Most simulation languages define single operations to represent the logic governing the flow of “entities” between “machines” or waiting in “queues”. In order to develop the model required from PETROBRAS ENERGIA was necessary to create new tools which allows aI.T RADITIONAL D ISCRETE E VENT S IMULATIONA.Simulating Discrete ManufacturingConcepts:Entities: discrete objects moving through the sistem Processes: generally representing machines or stations Resources: adds restrictions to the system, an entitiy has to seize e resource to perform an step to advance in the process Queues: waiting positionsLogic: control to the flow of entities among branches of the processFigure 1: Example of an elemental discrete processB.Simulating Continuous ProcessesConcepts:Tanks: represents continuous level of a fluid(levels) Flow: transference of fluid from one tank to another Valves: regulators of flows among different tanksLogic: opening and closing valves, is the way to control the transference of fluids through the systemFigure2: Example of an elemental continuous processTemplate for Modelling Refinery Logistics and Operation Using ARENAAuthors : Marcelo Moretti -PARAGON (Brasil), Luiz Augusto Franzese , Daniel Pablo Paz - PARAGONTECH LOGSIS (Argentina)Coauthor: Carlos Bacigalupo - PETROBRAS ENERGIAC.Templates in ARENATemplates allow to pack an important amount of logic, animation and data in a single object which is transparent to the user. Just defining its parameters for each new instance, an important amount of model logic may be reusable.The “Flow Process” template existing in ARENA, represent small parts of objects and operations related to fluid processing, however it requires an important effort to model the logic of a real world operation.Figure 3: Flow Process TemplateEach template “Element” is a black box that may be accessible to the user in different views:•Icon: represent the element to drag from thetemplate indo and drop into the model layout.•Dialog Window: allows the user to set theparameters defining an instance of the Element •Animation: is the form in which the elementwill appear in the model animation•Logic Block: is the form in which the elementwill appear in the model logicII.APPROACH TO THE PROBLEMA.Differences between refinery simulation and traditional manufacturing simulationAs traditional discrete process simulation deals with the definition o “entities” flowing through different machines and buffers, simulation languages are defined in terms of concepts that allows managing such entities. In the case of a Refinery Process, there are no “entities” the problem is how to manage the circulation of fluids according to a certain logic.It was necessary to create new elements to represent traditional simulation concepts into a continuous process. B.Understanding process conceptsIn traditional manufacturing the Workflow is very clear and very easy to understand jus standing for a while in front of the machines. The production line defines a Process very clearly. However, in a Refinery is impossible to understand a “typical workflow” in such a way. In facts a Refinery has a very big quantity of alternatives to move fluids from a tank to other tank, a very big quantity o operational variables.To represent the “Process Workflow” it is necessary to understand the “typical” operational alternatives, and represent the fluid transfer according to common operational practices, Additionally it is necessary to represent those processes involving Push or Pull policies for automatic refill, blending formulas, and interaction with the whole logistics system, for example, calling a Ship to dispatch products.C.Conceptualizing Fluid Processing ElementsThe general approach to represent each Element in a templateis:A variety of elements is represented as “tanks” which are controlled by a logic specific for the behavior of each kind of element. For instance: a valve or a tube will be essentially Tanks, but having a different control logic.D.Building ElementsTo build a useful template it was necessary to represent two kind of elements (like in discrete simulation)1.Real world physical objects: Tanks, Process Units,tubes, Valves, etc. Those objects have to be disposedon the process layout.2.Operational objects: transfer, blend, add fluid,remove fluid, etc. Those objects have to be arrangedin the logics that represent the typical operations ofthe plant.Template Elements: Real WorldTemplate Elements: Operational ObjectsE. Using ElementsTo build a model of a refinery, we begin to drag drop any real world object we find in the Process Workflow, like Tanks, ducts, and process units. We connect those objects using “tubes”.At the second step, we define the parameters of those elements Finally we have to represent the operational practices, which defines how the fluid will move though the process: by batch, continuously, push or pull.At the beginning and the end o this model we can connect traditional ARENA logic to represent the operation of transport units.III. R EAL APPLICATIONA. The Problem to SolvePetrobras Energia have to decide how to invest in new logistic assets in order to align its logistics system to a significant increase in Refining Capacity. It was no clear if an increase in production would be limited or not by the logistic system, and were to invest in order to provide such capacity.Previous experiences have allowed to model the shipping process, but no previous work or product have dealt with the logistic inside the refinery.The model to develop have to represent the flow, content and utilization of tanks, ducts, process units, docks, truck bays, and the restrictions of each operation.Additionally, the model to create will have to be easy tomodify by the user, in order to test different demand scenarios, supply schemes, plant capacity, tanks capacity, and operational policies.Additionally, this tool will have to be useful to represent the whole supply chain in Argentina, integrating the two refineries, several ports, transferences by ship and tucks dispatches, as well as a single plan operation in detail.B. Model’s Complexity1) San Lorenzo Refinery Process (Petrobras) To model this refinery was necessary to represent:Tank 80 Process Units 17 Tubes 140 Ducts 16 Auxiliar elements (manifolds, valves,etc) 35 Control Logics 180This would be virtually impossible or extraordinary extensive to model one by one. Therefore the template approach has allowed to do this effort in less than six months.2) Complexity, Extension an DetailThe total extension of this model involves the hole map of Argentina, arranging in it the different ports, storage stations and refineries. At the other side, the user needs to evaluate in detail a single Truck Loading process into a single plant.Because it is quite impossible to represent a very wide model with a high level of detail, the solution was to build the genera model and construct separated submodels when was necessary to analyze a single process in detail.The template created was useful to represent the global level, as well to represent the detailed level.3)Scenarios and AlternativesCombining the different demand scenarios, and investment alternatives, we would wave to create more than six different models.Additionally it was necessary to generate variations and sensibilities, to represent several operational alternatives, demand scenarios, in order to evaluate precisely the effects of any mayor investment or significant change in the operational logic.IV.C ONCLUSIONSuccess Dealing with ComplexityUsing a refinery template allows an organization to model very complex refinery process and logistics.It provides an intuitive way of documenting a dynamic representation of the refinery process.Less effortAdditionally, the model may be used b people with just a basic training in simulation, even to modify the process, and drastically reduces the time needed to build a model. FlexibilityIt results relatively easy to modify the process definition, operation logic and test different plant configurations and scenariosDesigning New PlantsIt may be a valuable tool to design new plants testing its whole operation before building them.A CKNOWLEDGMENTCarlos Gratti – Logistics Director, PETROBRAS ENERGIA (ARGENTINA)Alberto Martinez –Downstream Planning Manager , PETROBRAS ENERGIA (ARGENTINA)R EFERENCES[1]Simulation With Arena ; Sturrock,Kelton, Sadowsky,McGraw Hill 2006[2]Arons H. S.; Asperen E., Dekker R.; Polman M. (2004),Coordination in a Supply Chain for Bulk Chemicals,Proceedings of the 2004 Winter Simulation Conference., USA;[3]Ruiter, K. C. R.; Sluijs J. M.; Stoutjesdijk W. B. (2000),Simulation for Recurring Decisions, Proceedings of the2000 Winter Simulation Conference., USA;A UTHORSLUIZ AUGUSTO G. FRANZESE is Production Engineer ,and Master in Logistics. Is consultant in simulation, by now has successfully completed 150 projects in simulation, and trained more than 1.200 professionals in simulation.. Founded PARAGON Technologic in 1992, leading and pioneer company in simulation in Latin America. Contact: paragon@.br DANIEL P. PAZIs consultant in logistics, is Industrial Engnineer (U.N.Rosario, 1993),and Master in Business Administration (U. Barcelona, 1999). Has leaded the application of simulation in Argentina and other countries; working at TECHINT group until year 2000. Has recently founded with Luiz Franzese, PARAGONTECH LOGSIS S.R.L., first logistics simulation company in Argentina. He has founded the first exportation group of TIC’s of Argentina and conducted the Cluster of High Tech Companies “Polo Tecnologico Rosario” Contact: dpaz@.arMARCELO MORETTI FIORONI is consultant in simulation Electrical Engineer, Master in Production, and coursing Doctorate in Logistics. Is consultant in simulation, by now has sucessfully completed 150 projects in simulation, and trained more than 1.200 profesionals in simulation. Co-founder of PARAGON Tecnología in 1992.Teaches Operations Research and Simulation in Facultades Integradas de San Pablo (FISP). Contact: marcelo@.brC OAUTHORCARLOS MARIA BACIGALUPO is Chief of Schedulling and Planning of New Businesses at PETROBRAS ENERGIA.Bachelor in Marketing and MBA (U. Torcuato Di Tella, Buenos Aires). Has worked in Oil companes like Astra CAPSA, Repsol YPF y Petrobras Energía S.A. in several areas as New Businesses, Management Control, Planning. Contact: carlos.bacigalupo@。