This model is a proof-of-concept example demonstrating the integration of FlexSim with Python's Pyomo package to solve the Knapsack Problem. The model simulates a loading process of a logistic company. The truck has a weight capacity of 200 kg. The scenario includes 15 products, each with a specific weight and value. The product details are as follows: The objective is to determine which products to load onto the truck to maximize the total value of goods while ensuring the total weight does not exceed 200 kg. The ProductCreation Process Flow creates the products in a Queue. The General Process Flow has a Custom Code that creates a couple of Maps to store the products weights and values. It sets the capacity variable from the Parameters Table. These three parameters can be passed to python. Then it evaluates KnapsackProblem label on the Process Flow, passing those parameters in. The label is configured to connect to the KnapsackProblem function defined in the KnapsackProblem.py module. This function formulates the Knapsack Problem with Pyomo, solves the program, and then returns the optimal collection of products to be load onto the truck. Since the Decision Variables are binary, once the products are resolved, the values are stored in a Global Table, where 1 means that the product was selected. A Combiner uses this table to set the Component List. A forklift load the products and once completed, the truck leaves. When it enters the Sink a message is displayed showing the total weight and value loaded. Model Parameters There are two parameters that can be changed in this model. One is the Truck Capacity, which is the constraint of this problem. The value ranges from 100 to 300. There are three Global Tables in this model that store a different set of Weights and Values for each products. The table selected for the problem can also be changed using the GUI. Potential additions to this model could use priority for the products or include multiple trucks or constraints such as volume. Requirements to run the model In order to run this model, you need python properly configured, including: Install one of these python versions: 3.9, 3.10, 3.11 Install pyomo and highspy packages: python -m pip install pyomo highspy Make sure the python directory is part of your PATH environment variable. Configure your Global Preferences (the Code tab) to use the associated python version. This model was built in FlexSim 24.0 Knapsack_Problem.zip Troubleshooting If you are getting this error: exception: Code Binding Error: could not bind to function Node: /Tools/ProcessFlow/ProcessFlow>labels/KnapsackProblem Binding string: /**external python: */ /**/"KnapsackProblem"/**/ /** \nfunction name:*/ /**/"KnapsackProblem"/**/ Windows Error Code : 126 Check this post

Example Usage of the New AutoCAD FlexScript API The following example models were demonstrated at the Autodesk University presentation Elevating Factory Design: FlexSim and the Future of Autodesk Fusion Digital Factory. Refer to that presentation for a demo of these models and additional discussion regarding the topics demonstrated by these examples. These examples require the Autodesk Interop FlexSim Module. Healthcare Auto-Build Example Demo_AutoCadAPI_ER_4.fsm Using the new AutoCAD FlexScript API, the data within dwg files can be read using FlexScript to automatically build simulation objects within the model. The script in this Healthcare example is contained in the AutoBuildFromDwg() user command in the Toolbox. This command reads the average location of blocks on the Bed Layer to create Bed Location objects. It also reads the lines on the Wall Layer to automatically create Wall objects and connect them to the A* Navigator for automatic pathfinding around the walls. Reading dwg data string filePath = param(1); AutoCAD.Database db = AutoCAD.Database(filePath); if (!db)             return -1; var iter = db.getBlockTable().getAt("*MODEL_SPACE").newIterator(); for (iter.start(); !iter.done(); iter.step()) {             var ent = iter.getEntity();             print("Entity:", ent.layer, ent.objectType);             if (ent.layer == "Bed Layer") {                         if (ent.is(AutoCAD.Polyline)) {                                     AutoCAD.Polyline polyline = ent.as(AutoCAD.Polyline);                         }             } } Creating a bed location treenode bedConfig = library().find("/people/Objects/Location>behaviour/eventfunctions/configs/Bed"); Object obj = Object.create("People::Location"); function_s(obj, "changeShape", bedConfig); Creating walls Object walls = Model.find("Walls"); if (walls) walls.destroy(); walls = Object.create("People::Walls"); treenode wallsSurrogate = walls.find(">visual/drawsurrogate"); Object libraryPillar = node("/?Pillar", library()); Object newPillar1 = createinstance(libraryPillar, wallsSurrogate); newPillar1.setLocation(0.0, 0.0, 0.0); Object newPillar2 = createinstance(libraryPillar, wallsSurrogate); newPillar2.setLocation(10.0, 0.0, 0.0); function_s(walls, "addWall", newPillar1, newPillar2); Asserting the A* Navigator, a Grid, and connecting Walls Object walls = Model.find("Walls"); Object aStarNavigator = model().find("AStarNavigator"); if (!aStarNavigator) {             aStarNavigator = createinstance(library().find("?AStarNavigator"), model()); } Object grid = aStarNavigator.find("Grid1"); if (!grid) {             grid = function_s(aStarNavigator, "createGrid", 0, 0, 0, 1, 1, 0);             grid.name = "Grid1"; } contextdragconnection(grid, walls, "A"); AGV Read/Write Dynamic Blocks Example POC_OHT_3_MoveOHB.fsm POC_OHT_3_MoveOHB.dwg (If this file is named differently when you download it from Answers, make sure you name it back to this exact name. It is referenced by name in the model.) The script in this AGV example is contained in the interopAutoCAD() user command in the Toolbox. This command reads the location and names of particular dynamic blocks in the dwg file in order to automatically create AGV path simulation objects based on the configuration of each type of dynamic block. Additionally, the script has examples of both reading data and writing data back to the dwg based on modifications of the AGV paths within the simulation. The script is only partially complete as a demonstration of the API’s capabilities; the script is not a fully-working, robust solution for any arbitrary dwg. Factory Design Utilities Proof of Concept Example Demo_AutoCadAPI_FDU_1.fsm This FDU example model contains many user commands in the Toolbox with various functionality. The primary example starts in the Load FDU Layout button’s OnPress code. By default, it calls the AutoBuildFromDwg() user command. Alternatively, it has unreachable example code for calling AutoBuildFromLayout(), which can read the layout data from an FDU LayoutData xml file rather than a dwg file. The AutoBuildFromDwg() user command reads factory-specific meta-data about each FDU block in the dwg file and automatically creates simulation objects for each. The simulation objects then load the custom 3D shapes from FDU representing each of those objects. The import script also sets labels with the various Factory properties from each object. Within the CreateSimulationObjects() and CreateInternalObjects() user commands—called from the CreateFactoryAssetInstance() command—are hard-coded checks for particularly factory asset family ids to determine what type of simulation objects to create. This is merely a proof-of-concept example for handling FDU assets via FlexScript without any changes to FDU assets themselves. Future enhancements may include options for including such simulation meta-data within FDU assets directly for a more robust, easier-to-use solution. This workflow brings all the new Autodesk interop features together for an exciting, new way to bring factory data into FlexSim. Once that data is in FlexSim, you can use its many existing features to analyze the system with live 3D animation and dashboard charts showing simulation results. You can validate the throughput of the layout, identify potential bottlenecks, and balance resource use.

This article explores creating Fluid Tanks from a Basic FR and Process Flow. This turned out to be a lot more complicated than I thought. If you need fluid objects in FlexSim, use the standard fluid objects in the library or buy FloWorks. The approach in this article requires a lot of up-front work just to get started, and you probably want to spend that time configuring well-tested objects instead of cutting your own path. This article is directed at two audiences: Those who don't want to use the fluid library or FloWorks (they have elected the way of pain) Those who like learning from example models If you are still interested, read on! TankDemo_10.fsm Kinetic Tracked Variables Tracked Variables hold a number. As you change the value, the Tracked Variable tracks the min, max, average, etc. You can optionally track the history of the value over time (this history) or the amount of time spent at specific values (the profile). You can also listen to when a Tracked Variable changes. A special kind of Tracked Variable is a Kinetic Tracked Variable (KTV). A KTV lets you set a rate. The rate is the ratio of the change in value divided by the change in model time units. If you set a rate, the KTV records when you set the rate and the initial value. In this way, you can as a KTV for its value at any point and get the exact continuous value. KTVs are the heart of this model. You can use a KTV as a label value. Each tank has a label called "Level" that is a KTV that holds the level of the tank. They are also used to represent the progress of a transfer of fluid between tanks. Custom Draw The fluid tanks you see in the model are BasicFR objects. The shape of the object is set to a cylinder. The color of the object determines the color of the fluid. To draw the changing fluid level, the OnDraw trigger of the tanks use the Level label to determine the height of the fluid. Then the OnDraw trigger draws a cylinder covering the remainder of the tank. Because the draw code accesses the Level label's value, the cylinder will change as the value of the Level label changes. Tank: An Object Process Flow Most of the logic in this model is defined in an Object Process Flow called Tank. I used an Object Process Flow so that it would be easy to attach other objects to the flow to imbue them with fluid tank logic. In a way, it's like defining a programming class. When you attach an object, you create an instance of that class. The Tank flow defines behavior for a general fluid tank: A Tank can have fluid transferred in, out, or both A transfer indicates a source tank and a destination tank, and amount, and a rate. If the source tank is null, then the fluid is generated in the tank. If the destination tank is null, fluid is consumed in the tank. A tank can have as many active transfers as the user adds to it. There's not an accompanying concept of "pipes" in this setup. Each transfer changes the rate of the Level KTV for each tank. If the tank gets full, input transfers are paused until the the tank empties below a threshold (95% of its capacity). If the tank gets empty, output transfers are paused until the tank fills above a threshold (5% of its capacity). If the tank is stopped, both input and output transfers are paused until the tank is resumed. The Model Logic The model logic is contained in the process flow called Process Flow. It picks a random recipe from the Recipes table and uses that to create transfers into the Mixer tank. Once those transfers are complete, the Mixer tank empties itself. When it's completely empty, the tank produces an item. Then that process repeats. By using an Object Process Flow, the logic for "how to tanks work in general" is separated from "what are the tanks doing." Pros and Cons The main con is that you would need to implement this logic yourself rather than starting with an object. This includes finding and fixing bugs. I have found and fixed many bugs in this demo model, but I'm fairly confident there are more. It turns out creating an object is tricky. However, there are a few pros: Compared to the fluid library, there is no ticker. The fluid library relies on a ticker to handle changes in level. This approach uses KTVs instead. KTVs are newer than the fluid library. A ticker adds a frequent event to the model and loops through fluid objects checking for changes. It is possible that the approach in this article is more accurate and faster to run. It's also possible that it's slower, due to the number of process flow activities. Compared to FloWorks, there is no monetary cost. This may actually be a con as time spent developing logic is an expense. This approach will take 10x longer or worse to get right. Your future self will thank you for just buying it. You have full control over the behavior. If you don't like how something works, or you want to add additional logic, the logic is all available for you to edit. Again, this might be a con, because you have to fix bugs as you make them. Conclusion Overall, this demo model shows lots of FlexSim features working together. That is valuable in itself. As a replacement for fluid objects, this demo model isn't a great route, unless you have very specific needs. As I built this model, I realized that I was probably solving the same set of issues that the developers of the fluid library were solving. What I thought was going to be somewhat simple turned out more complicated. I still think this is doable, but I'd look at other options very carefully first.

When presenting and/or demonstrating a FlexSim model, it is often useful to have the model running in a loop that uses a flypath for a motion path. That way, you can more easily talk to the model while it runs, or leave it running unattended on repeat. The model below provides the code and settings needed to do that. In order to add this capability to your model, you will need to add a few things: A user event called EndTime. This setting will affect how long the model runs before resetting and running again. The First Event Time setting is where you can enter the number of seconds before this happens. The Event Code setting is where you can add custom code from the attached example model, found in the "event" tab. Model trigger code within OnRunStart and OnRunStop. This code can be found in the attached example model. A global variable called demo_mode. This can be set to 1 to enable the demo mode functionality, or set to 0 to disable it. Running the model with demo mode disabled is the same as how the model normally functions. Thanks to @Phil BoBo for helping to develop a solution for this. Also, the model requires FlexSim 23.2 or newer to work properly. presentation_demo_mode.fsm

This demo model shows the type of material handling logic that would be found in Bombay sorter system. This tiered conveyor system has products lined up in rows, then drop onto the next conveyor below while staying as a row. More a proof of concept than a fully-featured sample model, FlexSim users can use this as a springboard for more complex horizontal loop conveyor systems. A Bombay sorter (also known as a flat sorter) is a horizontal loop-style sorter. It's used for high-speed automated sortation of small, lightweight items, such as pharmaceuticals, books, and other small parcels. The chutes or cartons are located below the sorter, and when the product is in position, the doors swing open like a trap door to divert the product to the correct location. Bombay-sorter-demo.fsm

Note: the demo models were created specifically for the FlexSim user community who speak spanish, and all the explanations, statistics, and documentation available in the dashboard, GUIs, and Model Documentation are in Spanish. Nonetheless, given that 3D animation is a universal language, you are welcome to download these models regardless of the language you speak. Manipulación de material / Material handling Demo_Crossdocking.fsm En este modelo, llegan tres tipos de productos a dos zona de recepción. Un primer grupo de operarios se encarga de transportarlos a una zona de almacenamiento intermedio. Desde allí, otro grupo de operarios los clasifica según la ciudad a la que serán despachados. In this model, three types of products arrive at two reception areas. A first group of operators transports them to an intermediate storage area, where another group of workers sorts them according to the city they will be delivered to. Preparación de pedidos / Picking Demo_Picking.fsm En este modelo, los pedidos llegan de manera aleatoria a lo largo del día y son revisados y preparados por un operario. En este modelo, se puede modificar si los operarios realizan la preparación a pie o utilizando un vehículo, así como la ubicación del almacén de estibas y el número de operarios asignados. In this model, orders arrive randomly throughout the day, which are reviewed and prepared by an operator. In this model, you can change whether the operator does the picking on foot or using a vehicle, the location of the pallet zone, and the number of assigned operators. AGV - Vehículos de guiado automático Demo_AGV.fsm Este modelo demuestra la aplicación del módulo de AGVs de FlexSim, que permite simular sistemas que utilizan AGVs para el transporte automatizado de material. En este modelo, un AGV con capacidad para cinco productos se encarga de transportarlos entre dos zonas dentro de un proceso. This model demonstrates the application of the AGV module in FlexSim, which allows simulating systems that use AGVs for auomated material handling. In this model, an AGV with a capacity of five productos is responsible for transporting them between two zones within a process. Preparación de kits / Kitting Demo_Kitting.fsm Este modelo representa un proceso productivo que utiliza la técnica de preparación de pedidos. Mediante parámetros, es posible activar o desactivar estaciones de trabajo para evaluar el impacto en la productividad del proceso. This model represents a kitting process. Through parameters, it is possible to activate or deactivate workstations to evaluate the change in throughput statistics. Centro de vacunación / Vaccination center Demo_HC.fsm En este modelo se representan un sistema de atención de pacientes en un centro de vacunación. Los pacientes llegan de forma aleatoria, se registran y esperan hasta que una enfermera los vacune. This model represents a patient care system in a vaccination center. Patients arrive randomly, complete a registration process, and wait until they are vaccinated by a nurse. Cajero automático / ATM Demo_ATM.fsm En este modelo, se representan un sistema de retiro de dinero en cajeros automáticos (ATMs). Los usuarios llegan de forma aleatoria y realizan un retiro si hay un cajero disponible; de lo contrario ,esperan en la fila. This model represents a cash withdrawal system at ATMs. Users arrive randomly and proceed with a withdrawal if a cash machine is available; otherwise, they wait in line. Fluidos / Fluid Library Demo_Fluidos.fsm Este modelo representa un sistema de embotellado. Se generan, mezclan, procesan y finalmente embotellan dos tipos de fluidos. Después de embotellados, un operario los transporta a la zona de empaque. This model represents a bottling system. Two types of fluids are generated, mixed, processed, and finally bottled. After bottling, they are transported to the packaging area by an operator. Navegador GIS / GIS Navigator Demo_GIS.fsm Este modelo muestra cómo se utiliza el módulo GIS de FlexSim para determinar la ubicación óptima de un nuevo almacén, teniendo en cuenta una red de distribución específica. This model demonstrates how the GIS module of FlexSim is used to determined the optimal location for a new warehouse, considering a specific distribution network.

Last year a teacher asked me how to simulate public bus transportation, so I created a small sample model of a bus line in Nantes (France). Although all input and output data in the model are labeled in French, I thought that it could be nice to share it here with the worldwide community as 3D visualization is a universal language. Here is the model updated for FlexSim 2023: public_bus_23_0.fsm To set the travel times between the bus stops, and the stop times, I used the bus timetable that was available online in this document: Depliant-L-95-Web-2e.pdf You can check in the simulation if your bus arrives on time: Among the parameters, you can set how many buses are available at each terminus at the beginning. Be careful, if you don't have enough buses, you will not be able to stick to the timetable ! The road is built with network nodes. A checkbox allows you to show/hide the map. A listbox allows you to switch between the 3 network view modes (all details shown / edges only / hide all network).

This model shows a simple way of bringing together all the separate picks in an order to be consolidated in a putwall. It also shows a great way of tracking flowitems while on a conveyor through the use of tracked variable labels. A side concept is that the order reserves a slot in a rack for all of the picks. Conveyor-Routing-Order-Consolidation.fsm

Attached is a simple example of using the GIS Module. It contains a GIS Map with 8 Cities represented as points connected by driving routes. gis_example.fsm The model's Process Flow randomly generates tokens, which create items to be carried by trucks from one city to another. After a delay, the item is removed from the model. This very simple example demonstrates how to use the GIS Module to model movement of items from sources to destinations without any FixedResource objects. All the logic can be done through Process Flow to control what happens in the model. This model also demonstrates the Min Scale and Max Scale properties of a GIS Map object. By default, as you zoom the 3D view in and out, the 3D shapes on a GIS map scale so that they remain the same size on the screen, like abstract flat billboard images. When you zoom far out, because the items remain the same size, they seem really big relative to the map. Similarly, when you zoom far in, because the items remain the same size, they seem really small relative to the map. The Map object has Min Scale and Max Scale properties to cap the scaling up and down of objects as you zoom in and out, so that they will only scale up to a certain size and only scale down to a certain size. This makes it so they scale within a certain range, but don't get too big or too small. If you set both of these values to a particular number, then they will not scale at all, but rather be that particular size.

This model showcases the latest enhancements to the mass flow conveyor object, found in FlexSim 2023 Update 1. See several new features in action, including the Randomized fill order and Width Rules for conveyors. Mass-Flow-Bottling-Demo_23-1.fsm

This sample model shows the flexibility and power of the mass flow conveyor object. It contains many examples of stations found in this production process, from depalletizing glass bottles all the way through final packaging. The model makes use of many custom shapes that add realism and visual appeal to the simulation. Mass-Flow-Bottling-Line-Custom-Shapes.fsm