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Announcements, articles, and guides to help you take your simulations to the next level.
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Modeling LWBS patients is tricky business and can cause exception errors under certain circumstances if not done correctly. The problems usually arise due to patients who exit the model early while there are pending requests queued up in the model for future activities on the patient. The attached model demonstrates the current best practice for safely modeling LWBS patients without the possibility of generating unwanted errors. The modeling technique is very simply. Use the On Entry trigger of the waiting room object(s) to send a delayed message to itself in X minutes, where X is a sample time from an "impatience curve" representing the amount of time a typical patient is willing to wait before they strongly consider leaving. In the On Message trigger of the waiting room object(s), I have written a code snippet that you will want to copy and modify to suit your own modeling requirement. The code snippet in the example model checks to make sure the patient is still in the waiting room waiting for an exam room at the end of the "impatience time" when the message trigger fires. Then I roll the dice using a bernoulli distribution to decide whether or not to have the patient actually leave. The code snippet shows a different probability for each of two patient types (PCI's) and then a default probability of 50 percent for anyone else. Not only does this modeling approach avoid undesirable exception errors, but it is also more accurate and definitely more efficient than using the Quick Properties fields in the Patient Condition panel of a waiting room which requires repetitive function calls every so many minutes throughout the model run!
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Rápida demonstração de como usar o Graphical User Interface para controlar todo o modelo de simulação, desenvolver um painel de controle ou cockpit para alterar propriedades específicas de objetos dentro do modelo de simulação ou ainda, destruir ou recriar variáveis de objetos de forma a customizar ainda mais seu modelo. Tudo isso usando a estrutura do 'Tree' no FlexSim e também o recurso GUI, disponível no ícone em 'Tools'. Veja em nosso canal da FlexSim Brasil no Youtube.
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In this article, you will learn how to export data from individual replications to an external database. This is an advanced tutorial, and assumes some exposure to databases and SQL. It also assumes that you are familiar with the Experimenter and/or Optimizer feature in FlexSim. This tutorial uses PostgreSQL, but should be compatible with the most popular SQL database engines. Model Description Let's assume you have a model with at least one Statistics Collector, as well as an experiment ready to go. The model used in this example is fairly simple: As the model runs, a Statistics Collector fills in a table. The table makes a new row for every item that goes into the Sink, recording the time, and the Type label of the item: For the experiment, we don't have any variables, but we do have one Performance Measure: Input of the Sink. Of course, an actual model would have many Variables, Scenarios, and Performance Measures, but this model leaves out those details. For reasons which come up later, this model also has two global variables, called g_scenario and g_replication. We will use these during the experiment phase. Connecting to the Database To connect to a database, you can use the Database Connector tool. Each Database Connector handles the connection to a single database. If you need to connect to more than one database, you will need more than one Database Connector. For this model, I have added a Database Connector, and configured the connection tab as follows: This configuration allows me to connect to a PostgreSQL database called "flexsim_test" running on my computer at port 9001. You can test the connection by clicking the "Test Connection" button. The test attempts to connect, as well as query the list of tables found in the database. Setting Up the Export Next, take a look at the Export tab: This tab specifies that we are exporting data from StatisticsCollector1 to the table called experiment_results in the database (this table should exist before you set up the export). The Append to Table box means that when the export occurs, the data will be added to the table. Otherwise, the data would be cleared from the target table. The other interesting thing here is that we are exporting more columns than the Statistics Collector has, namely the Scenario and Replication number. However, the expression in the From FlexSim Column column must be valid FlexQL (FlexSim's internal SQL language). Wrapping the values in Math.floor() leaves the values unchanged, and works well with FlexQL. Setting up the Experimenter Finally, let's take a look at just a little bit of code that makes the Experimenter dump data to a database. There is code in Start of Experiment, Start of Replication, and End of Replication: In the Start of Experiment, we need to clear the table. The code in this trigger connects to the database, runs the necessary query, and the closes the connection to the database. In the Start of Replication trigger, the code simply copies the replication and scenario values into the global variables we created for this purpose. In the End of Replication trigger, the code uses function_s to call "exportAll" on the database connector that we created. This uses the settings on the Export tab to dump the data from StatisticsCollector1 to the database table, including the replication and scenario columns. These same triggers run during an optimization, so the same logic will apply. Run the Experiment Finally, you can run the experiment. When each replication ends, the Statistics Collector data will be exported to the database. Databases can handle many connections simultaneously. This is important, because the child processes that run replications will all open individual connections to the database at the end of each replication. This leads to many concurrent connections, which most databases are designed to handle. But how can we tell that it worked? If you connect to the database with another tool, you can see the result table. Note that there are 1700 rows, and that data from Replication 5 is included. Additionally, you could use the Import tab to import all the data, or summary of the data data, into FlexSim. Conclusion Storing data in a database during an experiment is not difficult to do. There are many excellent tools for analyzing and visualizing database tables, which you could then use to further explore and understand your system. postgresqlexperimentdemo.fsm
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En este video aprenderán a utilizar el objeto ASRS para representar el almacenamiento automatizado en estanterías. Para más videos tutoriales pueden suscribirse al canal de YouTube de FlexSim Andina y acceder a nuestra lista de reproducción de FlexTips.
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En este video aprenderán a utilizar diferentes estrategias de modelado para representar un cantidad de inventario inicial en el momento cero de una simulación. Para más videos tutoriales pueden suscribirse al canal de YouTube de FlexSim Andina y acceder a nuestra lista de reproducción de Retos FlexSim.
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En este video aprenderán a representar el uso de un montacargas con un operario. Este video está basado en esta pregunta del Foro. Para más videos tutoriales pueden suscribirse al canal de YouTube de FlexSim Andina y acceder a nuestra lista de reproducción de Retos FlexSim.
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En este video aprenderán a utilizar el Dispatcher para gestionar equipos de trabajo en un modelo de simulación. Para más videos tutoriales pueden suscribirse al canal de YouTube de FlexSim Andina y acceder a nuestra lista de reproducción de FlexTips.
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En este video aprenderán a representar fallas y/o averías en un modelo de simulación de FlexSim utilizando la tabla de MBTF/MTTR Para más videos tutoriales pueden suscribirse al canal de YouTube de FlexSim Andina y acceder a nuestra lista de reproducción de FlexTips.
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En este video aprenderán a utilizar el objeto Photo Eye para construir lógicas en un sistema de transporte de material automatizado con conveyors. Para más videos tutoriales pueden suscribirse al canal de YouTube de FlexSim Andina y acceder a nuestra lista de reproducción de FlexTips.
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En este video aprenderán a utilizar el objeto Station de FlexSim para representar demoras o procesos en un conveyor. Para más videos tutoriales pueden suscribirse al canal de YouTube de FlexSim Andina y acceder a nuestra lista de reproducción de FlexTips.
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En este video aprenderán a construir un modelo de simulación que representa un sistema de manipulación de material automatizado mediante conveyors. Para más videos tutoriales pueden suscribirse al canal de YouTube de FlexSim Andina y acceder a nuestra lista de reproducción de FlexTips.
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En este video aprenderemos a usar el ambiente de FlexSim HC para construir desde cero un modelo de atención de pacientes. Aprenderas a: Importar un plano de AutoCAD Crear objetos 3D Construir la lógica del modelo usando Process Flow Obtener estadísticas Diseñar un experimento Para más videos tutoriales pueden suscribirse al canal de YouTube de FlexSim Andina y acceder a nuestra lista de reproducción de FlexTips HC.
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En este video aprenderán el uso del Crane o Puente Grúa de FlexSim. Para más videos tutoriales pueden suscribirse al canal de YouTube de FlexSim Andina y acceder a nuestra lista de reproducción de FlexTips.
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En este video aprenderán la aplicación del objeto Traffic Control para prevenir colisiones entre Ejecutores de Tareas al utilizar Nodos de Red como navegador. Para más videos tutoriales pueden suscribirse al canal de YouTube de FlexSim Andina y acceder a nuestra lista de reproducción de FlexTips.
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En este video aprenderán a crear la lógica para cerrar o abrir un puerto de entrada o salida en base a una condición. Esa lógica se crea usando las operaciones de los Triggers de los objetos 3D. Para más videos tutoriales pueden suscribirse al canal de YouTube de FlexSim Andina y acceder a nuestra lista de reproducción de FlexTips.
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En este video aprenderán con gran detalle el proceso de minería de datos en Excel para extraer las cantidades y patrones de llegada de pacientes, para después importar estos datos en un modelo de simulación que utiliza eficazmente los datos para simular llegadas de pacientes realistas en un sistema de salud. Para más videos tutoriales pueden suscribirse al canal de YouTube de FlexSim Andina y acceder a nuestra lista de reproducción de FlexTips HC.
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En este video aprenderán el uso del objeto Robot de FlexSim. Para más videos tutoriales pueden suscribirse al canal de YouTube de FlexSim Andina y acceder a nuestra lista de reproducción de FlexTips.
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En este video aprenderán a usar la herramienta Paint Slot para crear etiquetas en los slots de almacenamiento de un Rack con el fin de establecer un sistema de almacenamiento condicional con la lógica 3D. Para más videos tutoriales pueden suscribirse al canal de YouTube de FlexSim Andina y acceder a nuestra lista de reproducción de FlexTips.
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En este video aprenderán a utilizar la herramienta Time Table para establecer turnos de trabajo en un modelo de simulación. Para más videos tutoriales pueden suscribirse al canal de YouTube de FlexSim Andina y acceder a nuestra lista de reproducción de FlexTips.
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En este video van a aprender cómo utilizar el objeto Separator para representar la división de FlowItems usando el modo Split. Para más videos tutoriales pueden acceder al canal de YouTube de FlexSim Andina y acceder a nuestra lista de reproducción de FlexTips.
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