A new feature has been added to our Answers Platform. In App notifications are now available for all users. These are instant notifications designed to work in coordination with or in place of email notifications. You'll now see a bell icon next to your avatar in the upper-right hand corner of your browser on the Answers website. In order for this location to start showing notifications, you will need to click on your avatar and choose 'My Preferences' Then click the Notifications tab in the top Navigation Bar. From here, you can choose to set certain actions to notify you instantly by selecting the radio button next to the action you would like to be notified on. Once there is content matching your notification settings, you'll see a red circle on the bell icon, as shown below: If you click the Bell icon, you will be redirected to a page showing all your recent notifications which will show you a summary of the notification as well as a link to the post:

Attached is an example model that simulates a Kiva system. kivasystem.fsm See Dev Talk: Kiva System Modeling for the steps I took in building the model.

The Statistics Collector is a powerful object. Its purpose is to record data about the model run as a table, and it is very effect at doing that. However, it is very abstract; being abstract allows it to be highly flexible, but makes it more difficult to learn. This article is meant to help you understand (or remember) how the Statistics Collector models the problem of converting model data from objects and events into a table of data. This article compares a Statistics Collector to a train being loaded an unloaded. It is NOT an article about how to model a trainyard or other rail-industry systems. The purpose is to compare the Statistics Collector, which is very abstract, to something most people understand. So we'll start by talking about the story of a simple freight train. This story has the following elements: Starting - the train starts its journey a the beginning of the line Loading Stops - the train makes several stops along the way to load goods Unload Planning - unlike a normal train, this train determines where it needs to go after this point based on what was loaded into the train Unloading Stops - the train makes several stops along the way to unload goods This is a very simple story. Just keep the sequence in mind - the train starts, makes several load stops, figures out its destinations, and then makes several unload stops. To see how this is like a Statistics Collector, take a look at this model: StatsCollectorVisualization.fsm This model is very simple. It consists of a Source, Queue, Processor, and a final Queue: Items are generated at the Source and flow through the Model. Items have a Type label, so that there are three Types of items: Type 1, Type 2, and Type 3. If you zoom out, you'll see a much bigger section of the model: This section simulates the logic of a Statistics Collector. As the model runs, you'll see AGVs run along the track, like a train. You'll see them make several stops and pick up boxes. Then you'll see them stop at the "Table" (the bigger black box in the image above) and "unload" data into the table. The Statistics Collector tool is a lot like this simulation. It has an internal "train", and you reference that train with the keyword data. When you use the Statistics Collector, you are configuring the journey of the train, which determines what data is recorded in your table. Starting the Train The statistics collector creates a train (the data object) when it observes an event. You configure which events a Statistics Collector cares about on the Events tab. You can listen to many different things, including: A flowitem enters or exits an object A token enters or exits an activity The model is reset The model gets to the warmup time Whenever any of these things happen, the Statistics Collector creates a train (again, called data) and starts it going on its journey. In this example, the Statistics Collector listens for items to enter Queue1. It also listens for items to exit the processor. Either event will start a train. Loading the Train Once the train is going, the Statistics Collector "loads" the train with information. In reality, this happens by adding labels and setting values on data. First, data gets all the values associated with the event (the event parameters) assigned as labels. Then, data gets all the labels specified in the "Additional Labels" section. Finally, data visits the Row Value station. Here, the special property called rowValue is set. Note that as you load the train, you can use anything already on the train to get more information loaded on train. In the example model, the row value is set to "data.item.Type"; data is the train, and the "item" label is already on board, so the row value field can use that to load additional information. Unload Planning The next stop for the train is something that you can't really see, but that is very important. The Statistics Collector inspects the row value on data. The Statistics Collector remembers all row values that it has ever inspected, and it adds a row to the table for each unique row value. This is where the row value got its name. If the Statistics Collector sees a value it has never seen before, it adds a row to the table, and associates the new row with the row value. Once the row is either added or found, the Statistics Collector sets the property rowNum on data. So now, the train knows which row it is going to visit. All that is left in this phase is to figure out which columns the train will visit. First of all, if the row was added, the train will visit all the columns to set their initial value, which is called the Row Add Value (the value to set when the row is added). Whether or not the row was added by the event, the train will also visit any columns that are connected to the event, setting the value to the Event Value (the value to set when a connected event happens). So in summary, the Statistics Collector figures out which row the train will visit based on the row value, adding a row if necessary. If the row was added, then the train visits all columns in the row, to set the Row Add Value. If the event is connected to any columns, the train will also visit those columns, and set the Event Value. Unloading the Train Finally the train can unload data into the table. As it visits each cell, it unloads information into that cell. As the user, you configure what gets unloaded at each cell. You can unload anything into the cell, including anything on the train, anything connected to anything on the train, or anything globally accessible. In reality, whenever the Row Value or Event Value is evaluated, you can access and labels or properties on data. You can also use values on data to access other values. Or you can access global values, such as the current model time, or a Global Variable, or a value in a Global Table. In the example model, the Event Value field accesses the value that is currently in the table at the cell being visited by data. Does the statistics collector really have to travel? In the visualization model, the data train takes up time on the clock to load, plan, and unload. However, for the true Statistics Collector, all of that happens in zero time. For example, when an item enters Queue1, the real statistics collector in the model finishes updating instantaneously. In contrast, the visualized statistics collector train is still moving to get more labels. This is for illustration purposes only. What about "Update when accessed" columns? All Statistics Collectors know when something is trying to read their values. For example, if you have a chart pointed at a Statistics Collector, and that chart repaints, it will read the Statistics Collector. Or if you access the table through FlexScript with code like Table("MyStatisticsCollector")[1][1], that will read the Statistics Collector also. So in a way, it's just another event. However, there are two differences: You can't load custom labels on the train for this event; it "skips" those stops The train visits all rows in the table When you set a column to update when the value is accessed, you are basically connecting it the "OnAccess" event. So when the table is accessed, the data train visits all rows of the table. For each row, it gets the rowValue and rowNum properties set, and then it visits all the "update on access" columns. What about other features? This article just covers the basics, and doesn't cover other features of the Statistics Collector. Just know that there are many ways to configure the train's journey. For a full reference, see https://docs.flexsim.com/en/21.0/Reference/Tools/StatisticsCollector/ However, all of the features discussed in the reference add more detail; you can just improve your mental image of how the Statistics Collector works.

FlexSim 2021 Update 2 Beta is now available (Updated 26 July 2021) To get the beta, log in to your account at https://account.flexsim.com, then go to the Downloads section, and click on More Versions. It will be at the top of the list. The More Versions button does not appear when logged in as a guest account. Subsequently the beta is available only to licensed accounts and accounts that have a license shared with them. Learn more about downloading the best version of FlexSim for your license here. If you have bug reports or other feedback on the software, please email dev@flexsim.com or create a new idea in the Development space. FlexSim 21.2.0 Release Notes Added a Template system for inheriting properties from other objects. Added new manipulation handles for moving, rotating, scaling, and connecting objects in the 3D view. Added ability to delete connector lines. Added a StateTable object. Added a getstatetableutilization() command. Added a Pass-through parameter type. Added a checkbox so transporters can move their forks separate from traveling. Added more Task Executer shapes. Improved treenode.getPath() to return a relative path to nodes that aren't a direct ancestor. Added a Frustrum Culling checkbox in Visuals. Agent Added an AgentSystems property. AGV Allowed the user to define some basic routing cost multipliers, including: An option to divide by speed, allowing for fastest path routing (instead of shortest path) An option to define a custom path-based multiplier to the cost Added Path Conditions, which allow you to "close" certain paths, based on either model state or agv state, etc. Added a Prioritize Control Point Lookahead option. A* Added the capability to have oblong grid node sizes. Allowed barriers to be inside visual tools. Added the ability to add dynamic barriers to the A* system. This is done by calling AStar.navigator.addDynamicBarrier(), then AStar.navigator.removeDynamicBarrier() to remove those barriers. Added several triggers to A* objects: AStar.Navigator: OnGridChange: called when dynamic barriers are added or removed AStar.Traveler: OnCalculatePath: called just before a traveler's path is being calculated AStar.Traveler: OnNavigatePath: Called just before a traveler runs the algorithm to define kinematics and cell allocations for traveling its path. Also allows the ability to override the default behavior and define your own. Made several additions to AStar.Traveler API, AStar.Navigator API, etc. Added a TravelPatterns property. Backwards Compatibility Note: The following changes may slightly change the way updated models behave. Improved the deadlock recovery algorithm. Now it will add each traveler in the deadlock, as well as any travelers that are waiting on those travelers, as dynamic barriers. Then it will go through each traveler in the deadlock, remove it from the dynamic barriers, add any additional travelers that are adjacent to that traveler as barriers, then try to recalculate the path to the traveler's destination. If it finds a traveler that can still travel all the way to its destination, that traveler will be rerouted. Otherwise, if it finds a traveler that can travel at least on grid square, it will reroute that traveler. Otherwise, it will give a notification of unrecoverable deadlock. GIS Added the GIS module to the Flexsim Installer. Process Flow Added a ProcessFlows property. Added a ProcessFlowVariables property. Backwards Compatibility Note: The following changes may slightly change the way updated models behave. Removed instance object editing from Object Process Flows.

Greetings, I would like to share my latest FlexSim creation with the community, HUGE thank you to the flexsim overlords for creating such an awsome software https://youtu.be/WyfNS6vfLZE. G

I have created the following model to use elevator for different floor. I am not sure what I have missed out that the elevator is not working. Please advise me. Thanks multi-floor.fsm David

FlexSim 2020 Update 2 is available. If you have bug reports or other feedback on the software, please email dev@flexsim.com or create a new idea in the Development space. Release Notes Updated the run speed slider so you can customize the ratio of display units to real seconds. Moved object properties windows into the context sensitive Properties window (formerly known as Quick Properties). Added a new Quick Properties window that appears next to your cursor when double clicking on an object. Added a pop-out button to the Labels panel of the Properties window. Added a Dark theme for FlexSim's UI. Removed help manual from the installer and linked help to docs.flexsim.com. Created a separate installer for a local help manual. Added Unit edit buttons to more edit fields. Updated the Quick Library to match the current state of collapsed and expanded panels in the main library. Removed the View Settings window and moved all its options into the Properties window. Improved performance of Properties window and various other UIs. Added Object Property tables. Added Object class properties and methods to the Variant class in FlexScript. This removes the need to use .as(Object) if you know the treenode pointed at by a Variant is an Object. Added Object.resetPosition property. Added capture groups to the string.replace() method. Enabled several SQL clauses - NOT, NOT IN, DELETE FROM, INSERT INTO, and LEFT JOIN/LEFT OUTER JOIN. Added ARRAY_VAL() sql function for accessing a value in an array. Added unit conversions to the convert() command - convert(4.5, "ft/min", MODEL_UNITS). Improved performance of loading media by making it multi-threaded. Updated the default web server 3D view to stream using WebGL data instead of video. Added Color.fromPalette options to several Set Color popups. Added a pickoption for the Source's On Creation trigger for attaching items to an Object process flow. Disabled the beeping noise when pressing Enter in edit fields. Fixed the Create Object edit mode sometimes not creating objects and just exiting (like when clicking on the library when the User Manual was active). Fixed a draw issue with tables drawing bold text sometimes. Fixed a bug with window docking. Backwards Compatibility Note: the following changes may slightly change the way updated models behave. Changed updatehotlinks() to only repaint the view if it applies a node with a viewsyncupdate attribute of 1. The keywords VALUES an DELETE were added to the sql parser. This means that previous models that use the term VALUES, Values, values, DELETE, etc. will get an error because sql now sees it as a special keyword. If you get this error, just wrap your term with square brackets: [Values] to tell the parser to not interpret it as a sql keyword. Agent Added the Agent module to the Flexsim Installer. Enabled A* walls as static agents. Added a neighbors() function to the Agent API. Fixed social forces for agents not in model space. Fixed bugs with using A* bridges. AGV The join tool now joins in all cases, defaulting to a straight path if it can't solve for a curved path. Conveyor The join tool now joins in all cases, defaulting to a straight conveyor if it can't solve for a curved conveyor. Emulation Added Allen-Bradley connections. People Improved performance of state history tables. Fixed listening to travel events on a person created with the Create Person activity. Process Flow Added new Kinematics activities. Added new Warehousing activities. Added an Enabled checkbox to the Source activities so that you can turn them off. Consolidated Fixed Resource and Task Executer process flow types into a single "Object" type. Added a right-click menu option to the 3D view so a user can right-click on an object and add an Object process flow directly. Added an Object Flow field to the Create Object activity and added a pickoption for attaching items to an instanced flow. Changed double clicking on an activity to be more consistent with the 3D view and now opens the activity's properties window. This window now has a name edit field so you can still easily rename the activity. You can also slow double click to only open the old name edit field. Improved performance of activity properties windows.

FlexSim has been taught in hundreds of universities, both as the subject of full simulation courses and also as short course modules. Professors who teach these courses expect that their FlexSim-related assignments will be completed with a high level of academic integrity. FlexSim has also been used for many capstone, thesis, and dissertation projects, all of which fall under the university’s academic honor code (or honor system). FlexSim is committed to help maintain a high level of integrity in the academic assignments and projects that pass through our support department. We’ve created a list of guidelines for academic modeling using FlexSim: Those Using FlexSim for Academic Purposes Can... Access our extensive product documentation (https://docs.flexsim.com) Utilize the FlexSim Primer (by Dr. Allen Greenwood), which is a great starting resource for learning FlexSim and was developed specifically for academia—download it at https://flexs.im/primer Access papers, videos, and other FlexSim-related documents that are publicly available Search the entire database of questions and answers that have been posted publicly on FlexSim Answers FlexSim Will Not… Complete any portion of an assignment or project which falls under an academic honor code Write custom code as part of an academic assignment or project Share answers or model results from the textbook Applied Simulation: Modeling and Analysis Using FlexSim to anyone except educators teaching the material Otherwise aid in activities that circumvent the academic integrity of an assignment or project

I was recently asked how a user can implement jerk, i.e. a rate of acceleration change, in the AGV module. The AGV module uses FlexSim's kinematics API to define the motion of AGVs along paths. The kinematics API does not natively support jerk. However, the AGV module has included a hook to allow developers, and audacious end users :-), to customize the kinematics that drive AGVs on paths. Using this hook, you can approximate jerk by breaking what would otherwise be a single kinematic, with a single acceleration/deceleration, into multiple smaller kinematics that gradually change the acceleration/deceleration of the object as it progresses. There are two ways to do this. The first option is to simply do it as an end user, confining your changes to your model, by customizing nodes in the tree. The second option is to do it as a module developer, using the module SDK. Adding Jerk as a User The AGV network uses an "AGV Customization Delegate" to allow for hooks to be placed at certain points in the AGV navigation logic. There is a default customization delegate that the AGV network uses, but you can override the logic of this default delegate by adding and configuring a special node at MODEL:/AGVNetwork>variables/customizationDelegate. But before I tell you how to do it, I want to explain a little more about how it works. I've attached three C++ files. The main ones you'll want to look at are AGVCustomizationDelegate.h and AGVCustomizationDelegate.cpp. These show the definition of the customization delegate class. In the header file, you'll see the definition of AGVCustomizationDelegate class. This class includes several methods, but the main method relevant here is addKinematics(). This method takes several parameters defining the context. Its responsibility is to add one or more kinematics, in the positive X direction, that will move the AGV the target distance along a path. The AGVCustomizationDelegate class is the default customization delegate used by the AGV network. The C++ files also define a subclass called UserAGVCustomizationDelegate, which overrides the methods of its parent class by delegating the logic to FlexScript code that the user can write in the model. So, now for actually doing it in the model. We want to instantiate an instance of UserCustomizationDelegate at the node MODEL:/AGVNetwork>variables/customizationDelegate, so that we can write FlexScript code to add the kinematics. Navigate in the tree to MODEL:/AGVNetwork>variables/customizationDelegate Right click on that node, and choose Edit > Designate this Node (so) In a script window execute the script: nodeadddata(so(), DATATYPE_SIMPLE) Add a subnode to that node named sdt::attributetree and give it the text: AGV::UserAGVCustomizationDelegate. Copy the node and then paste it onto itself. This will instantiate the UserAGVCustomizationDelegate. Right-click on the addKinematics subnode and choose Build > Toggle Node as FlexScript. Right-click on the addKinematics node and choose Explore > As Code. This will allow you to edit the code for adding kinematics. The header for field should be as follows (note this is determined by the evaluate() command in AGVCustomizationDelegate.cpp at line 71). treenode kinematics = param(1); // the kinematics node to call addkinematic()/getkinematics() on treenode section = param(2); // the associated travel path section double startAtTravelDist = param(3); // the agv cumulative travel distance at this point double distance = param(4); // the distance to travel on the path section (your addkinematics() calls should add up to this distance) double startTime = param(5); // the start time for the first addkinematic() call double startSpeed = param(6); // the initial speed to start at double endSpeed = param(7); // the target end speed (should be going this speed at the end) int reason = param(8); // reason for adding the kinematic (see AGVCustomizationDelegate.h) treenode endSpeedOut = param(9); // if target end speed cannot be reached, update this node's value with the actual end speed double peakSpeed = param(10); double acc = param(11); double dec = param(12); TaskExecuter agv = ownerobject(tonode(get(kinematics.up))); // the agv At this point you can customize how kinematics are added to the kinematics node in this code. To approximate jerk you would break it up into small addkinematic() commands that each change the acceleration/deceleration. Please refer to the kinematics api for more information on how to manipulate kinematics. Note that you should only use the addkinematic() and getkinematics() commands in this field (not initkinematics() or updatekinematics()), and the addkinematic() command should only tell the AGV to move forward in the X direction. Y and Z directions are ignored by the AGV travel logic. In other words, from a kinematics perspective, the AGV network "flattens" an AGV's path into movement in a straight line along the x axis. When you're finished adding kinematics, you should return the end time of the last added kinematic. This will be the same as the return value of the last called addkinematic() command. Adding Jerk as a Module Developer To implement jerk as a module developer, you would first create a module using the module SDK. Then you would include AGVClasses.h and AGVCustomizationDelegate.h in your project (do not include AGVCustomizationDelegate.cpp as it won't compile properly. I'm including that file just to be informative in this article). Then you would subclass AGVCustomizationDelegate with your own class that overrides the appropriate methods, specifically the addKinematics() method. Once you've done that, you would replace MODEL:/AGVNetwork>variables/customizationDelegate with an instance of your customized class, using the same steps described above, but using your own class name instead of AGV::UserAGVCustomizationDelegate. If you need more header files so you can access more information, i.e. the definition of TravelPathSection, the let us know and we can get them to you. agvheaderfiles.zip

Following attached Code is Useful as Performance Major to Find Out Total Simulation Time in Different Scenarios. treenode datanode = param(1); double tm = time(); return tm;

We recently had a customer ask how to draw a flow item label on the flow item object. I thought that this information would be useful to other FlexSim users as well. In the 3D model, drag and drop a Text visual from the Library. Select the text in the 3D model, then copy it to the clipboard using Ctl + C Go to the Toolbox tab, open the FlowItem Bin, and double click the Flow Item of interest. Right click the 3D flow object, and click "Explore Tree" Click in the white space underneath the Flow Item's node, and use Ctl + V to paste the text as a subnode to the flow item. If you zoom out in the Flow Item's 3D view, you will see the text. You can double click on the text and use the General tab to position it wherever you would like. Double click the 3D Flow Item. Underneath the Labels tab, select the green plus sign to add your label. In my example, I added a number label called "Type" with a default setting of 0. Click "OK". Double click the text that you added in step 5 and 6. Underneath the Display tab, click the custom code button next to Text Display. Within the custom code type something like the following: /**Custom Code*/ Object current = ownerobject(c); treenode textnode = param(1); textnode.value = "Type: " + string.fromNum(current.up.Type); //Note: If your label is called something other than "Type", make sure to replace it in both places. Click out of the "FlowItem Bin" tab and back into the "Model" tab. Double click the source where your Flow Item is being created. Underneath the Triggers tab, add an On Creation trigger. Click the green plus next to the On Creation trigger. Hover over Data and select "Set Label". Make sure the text next to the Label field matches the text of the label you set in step 7 and 8. By following these steps, each Flow Item will have a text label that displays the Flow Item label next to the Flow Item object. Please see the attached gif for a demonstration. flowitem-label.gif

Run FlexSim "in the cloud"? Instead of provisioning a desktop or laptop PC that meets FlexSim's recommended system requirements, you may prefer for your FlexSim users to use a thin client PC which connects to a more powerful back end system that actually runs FlexSim. FlexSim does not test our products in such environments, so your user experience may vary. Meet the system requirements It is important that the remote system meet or exceed FlexSim's recommended system requirements. Usually for CPU and RAM that is not a problem. In the past, the biggest hurdle was typically graphics. Does the remote machine support hardware accelerated graphics, and support streaming those graphics to the thin client where the user is actually sitting? If the graphics are not accelerated, or if accelerated graphics can't be streamed to the user, then the system doesn't meet FlexSim's requirements and you may have a bad user experience. In the past In the past, provisioning such a system to meet FlexSim's requirements was quite a specialized combination of hardware and software. Even today not every cloud provider has the infrastructure to stream accelerated graphics. Our anecdotal experience is that such set ups are becoming more common among 3rd party cloud providers. Going forward Major players now seem to have mainstream support for hardware accelerated graphics: https://aws.amazon.com/ec2/elastic-graphics/ https://docs.microsoft.com/en-us/azure/virtual-machines/windows/sizes-gpu https://cloud.google.com/gpu/ As mentioned above, FlexSim is not targeted to these environments and the software is not tested in these environments, so your mileage may vary. Conclusion With more and more cloud providers enabling hardware accelerated graphics, there is a chance that FlexSim could work well on a cloud-based platform. If you have tried running FlexSim remotely using one of these or another cloud provider, we'd love to hear your experience. Please comment below to let us know about your setup, what worked, and what didn't.

This article borrows from @jordan.johnson's original guide for deploying a distributed experiment/optimization with Amazon. Distributed Terminology Please be familiar with the terminology related to experiments and optimizations. Replication - a distinct model run. We'll use this term below for both replications (experimenter) and solutions (optimizer). Instance - a system, whether virtual or bare-metal, local or remote, meeting FlexSim's recommended requirements, and used for running distributed replications. Main PC - the system from which the user configures and initiates the distributed experiment or optimization. The Cloud - a shorthand term for remote servers/systems hosted in a data center, sometimes by a 3rd party such as Amazon, Microsoft, Google, or others. Background Concepts In discussing distributed experiments or optimization, you should start with a good understanding of both the Experimenter and the Optimizer. Please read and understand this user manual entry which includes explanations of key concepts that will be important as you continue. Other user manual articles provide additional guidance on configuring your own experiments or optimizations. Search the online user manual and this community if you have additional questions regarding experiments or optimizations, as needed. Using the experimenter requires a FlexSim license. The optimizer requires a license for the OptQuest add-on. Please contact your local distributor for more information or to request a test license for FlexSim and/or OptQuest. What are distributed experiments or optimizations? Experiments or optimizations can create dozens, hundreds, or even thousands of distinct model runs (or replications) to test various scenarios, build confidence intervals of the results, or zero-in on an optimal solution. A distributed experiment or optimization takes those individual model runs and assigns them (distributes them) to run across a group of computers. If you needed to run 1000 replications, and you have 4 computers available, each computer could run 250 replications, getting your results 4 times faster. When should you distribute? Using distributed replications can significantly reduce the required time to run an experiment if: The single-run time for your model is high (a couple minutes or more) You anticipate running a high number of replications If the time per replication is short, then the increased communication overhead may outweigh the benefit of using distributed replications. The communication overhead increases because all distributed replications still report results to a single FlexSim process on the Main PC, and that communication occurs over the network (local instances) or internet (remote instances), rather than on a single computer. If an experiment or optimization completes in an acceptable amount of time, you may not need to use distributed replications. Financial Costs 3rd party cloud providers such as Amazon, Microsoft, Google, and others, charge for their services. Your cost is usually based on the hardware you provision for your Windows instances, and the length of time those instances are live. Typically you only run your instances when running your experiment or optimization, and cancel or decommission your instances when your replications are complete. In this way you minimize the cost of your distributed experiment or optimization. The costs and process of decommissioning your provisioned instances differ based on which 3rd party cloud provider you use. You may have access to local computing resources that could be configured for use in your FlexSim experiments or optimizations. In this case you may avoid additional costs relating to 3rd party cloud providers by using your own on-premises computers. Licensing for distributed Windows instances Windows instances used solely for distributed replications DO NOT need an individual FlexSim license. Only the FlexSim installation on the Main PC must be licensed. System requirements for distributed Windows instances Graphics A Windows instance should meet or exceed FlexSim's recommended requirements. However, because replications run as background processes without graphics, they need not meet the graphics requirements and do not need hardware accelerated graphics. CPU An instance can run as many concurrent replications as it has CPU cores. If, for example, an instance has 32 CPU cores, it can run 32 replications of your model simultaneously. RAM For this example of a 32-CPU Windows instance, if you want FlexSim to run 32 replications simultaneously - one on each core - then the instance must also have enough RAM to handle 32 concurrent model runs. On your Main PC, use Windows Task Manager to watch a single model run's RAM usage to determine its peak RAM utilization. If your model's RAM utilization peaks at 3GB throughout the course of a model run, you should make sure your 32-CPU system has at least 32*3 = 96GB of RAM for replications alone, along with a good ~10% more for additional overhead used for the Webserver and the statistics gathering and reporting from all the replications (this number could be more or less, depending on the model's stats gathering). In addition, you must account for your system's baseline RAM utilization - how much RAM it uses just to run the operating system and all its background processes. You can find this baseline by checking the Task Manager at a moment when you're not running any simulations. Add all these together to see how much RAM would be necessary to run a replication on each core of the instance. If your instance doesn't have enough RAM to handle that many simultaneous replications, you'll need to limit the number of CPUs FlexSim will use when configuring your Cloud Computing settings from the Main PC. Disk Disk space is usually not an issue. However, if you are using the Store Data on Hard Drive option in the Statistics Collector, you will need to be sure that there is enough disk space to run the model to completion on the hard drive, multiplied by the number of cores. The amount of disk space on each instance may affect the total cost of using a 3rd party cloud provider. More information See the related sections in the article Recommended System Requirements for a more in-depth discussion of system components such as CPU and RAM, and how they relate to running your simulations and experiments. Provisioning distributed Windows instances The process of provisioning 3rd party cloud instances for running distributed FlexSim replications will differ from provider to provider. FlexSim has guides for the following cloud providers: Amazon Web Services Wherever you decide to host your instances, the important part is that eventually you end up with a group of Windows instances, each with a unique IPv4 address accessible from the Main PC. A custom Windows image Your 3rd party cloud provider probably allows you to save a custom Windows image that can include software and settings that you need for each Windows instance. Doing this once for a custom Windows image saves you time when starting new instances - each instance will start with the software and settings preconfigured for your purpose. On your custom image, do the following Download and install FlexSim. Use the same version of FlexSim as is licensed on the Main PC. Remember, you DO NOT need to activate a license. Run FlexSim. This creates a directory that is needed later. After FlexSim finishes its first start, close FlexSim. Download and install the FlexSim Webserver for your installed version of FlexSim. Edit the Webserver's configuration file appropriately for your situation. Default location is here: "C:\Program Files (x86)\FlexSim Web Server\flexsim webserver configuration.txt" Start the FlexSim Webserver from your Windows Start menu, or manually from the default location here: "C:\Program Files (x86)\FlexSim Web Server\flexsimserver.bat". The Webserver will download necessary files the first time it is run. Close the Webserver after it has completed its initial startup. Allow both FlexSim and node.js through the Windows Firewall. To do so, use Windows' Allow an App through the Windows Firewall tool. You will need to browse for both FlexSim and Node.js. Example locations (exact locations may vary by version): C:\Program Files\FlexSim 2023\program\flexsim.exe C:\Program Files\nodejs\node.exe If you are not familiar with the FlexSim Webserver, please review its documentation and test it out on a local machine to understand what it does, its configuration options, etc. If you cannot configure a custom Windows image, you will need to do the above on each instance individually. Initialize instances Launch your instances. On each instance, do the following: Log in to the instance with Remote Desktop or some other solution. Start the FlexSim Webserver from your Windows Start menu, or manually from the default location here: "C:\Program Files (x86)\FlexSim Web Server\flexsimserver.bat". Note the instance's IPv4 address. Once all instances are running the Webserver, you are ready to configure a distributed experiment or optimization from the Main PC. Author's Note: There is probably a way to make it so that when instances start up, they automatically run the Webserver, so that you don't have to manually connect to each one. I welcome any suggestions or steps for how to make that happen. Configuring a distributed experiment or optimization Once you have a list of running instances available, launch FlexSim on the Main PC. Open the experimenter interface from FlexSim's Main Menu > Statistics > Experimenter. Configure your experiment. As part of your configuration, under the Advanced tab, select the option to Use Distributed CPUs. Press the button to Configure Cloud Nodes. This will open the Global Preferences' Environment tab. Enter the IP addresses of your instances into FlexSim. Enter the port numbers you configured in their FlexSim Webservers. If your instances will max out RAM before CPUs, enter a CPU count representing the maximum number of concurrent replications your instance can handle. For more information on using remote computers for Experiment Jobs, see Running Jobs on the Cloud for more information.

FlexSim 2019 Beta is available. (Updated 21 December 2018) To get the beta, log in to your account at www.flexsim.com, then go to the Downloads section, and click on More Versions. It will be at the top of the list. If you have bug reports or other feedback on the software, please email dev@flexsim.com or create a new idea in the Development space. Release Notes Added support for importing JT files. Added a way to directly animate 3D shapes with bones. Added a way to parent subcomponents to a bone on a 3D shape. Updated calculated tables and chart templates to be able to save their data during an experiment. Added support for SQL keywords UNION, UNION ALL, INTERSECT, and EXCEPT. Updated the time table's weekly and daily modes to use a graphical display. Improved the time table's user interface. Added options for stacking bars on a histogram and added more bar modes. Added a Column Sets feature to statistics collectors. Added more options for event listening in statistics collectors. Added an option to statistics collectors and calculated tables for object path display depth. Added an option to statistics collectors to stop tracking row values after specified events. Added an option to milestone collectors to start new entries on the next milestone. Added options to record more data in additional columns on a milestone collector. Added enable/disable right-click menu options to statistics collectors in the toolbox. Improved the performance of calculated tables in certain configurations. Fixed a bug with Always Leave Entries on List when reevaluating multiple back orders. Fixed a bug with color spilling from one mesh to another when using shape data overrides. Fixed scaling issues and a crashing bug when loading certain STEP and IGES files. Process Flow Improved the Token.create() method to be able to create child tokens. Added a new Person Flow type of Process Flow. Fixed a bug with a resource connected to a global list deleting the list when the resource was in an instanced flow. People Added a Process activity. Added a Remove Person activity. Added various activity sets to quickly create common groups of activities. Added a priority value to resource objects that is used for acquiring and preempting resources. Added advanced options to the Process activity for handling preemption. Added functionality for simulating shift schedules with time tables and down behaviors. Improved the UI for how people objects are added to groups. AGV Improved control point selection on paths in the 3D view. A* Added a way to draw a heat map based on a node's percentage of total traversals. Added a Two Way option to preferred paths and dividers. Added a Condition option to A* objects to optionally disable them under certain circumstances. Added a Mandatory Path object used for defining sets of paths where certain connected objects can travel. Updated the Barrier object to be able to specify patterns to determine how it affects the grid. Added a FlexScript API for A* objects and data. Backwards Compatibility Note: the following changes may slightly change the way updated models behave. Fixed a bug with A* barriers blocking space larger than their actual size.

One of the new features in FlexSim 2018 Update 2 is the ability to use distributed CPUs for the Experimenter or Optimizer. Those cores can exist on any machine that meets the following requirements: The machine is accessible by IPv4 address The machine has FlexSim installed The machine is running the FlexSim Webserver (version 18.2.0 or later) on port 80 The machine meets hardware requirements to support running the specified number of simultaneous replications. This article describes how to use Amazon Web Services to create remote machines that meet the above requirements. Using AWS, you can launch and connect to as many servers as you want, and pay only for the time used on those instances. Anticipated Use Case Using distributed CPUs can significantly reduce the required time to run an experiment if: The time to run a single replication is high (a couple minutes or more) The number of replications to run is high If the time per replication is short, then the increased communication overhead may outweigh the benefit of using distributed CPUs. The communication overhead increases because all CPUs still report results to a single FlexSim process, and that communication occurs over the internet, rather than on a single machine. If an Experiment or Optimization completes in an acceptable amount of time, you may not need to use distributed CPUs. Financial Costs Amazon charges for its services. Costs for running instances (and transferring data out of them) are found here : https://aws.amazon.com/ec2/pricing/on-demand/ Costs for storing data (including AMIs) are found here: https://aws.amazon.com/ebs/pricing/ These instructions include steps to create an AMI, which will likely cost around $1 per month at current rates. It also includes steps for launching high-performance instances, which have an hourly cost. Suitable instances can be as cheap as $0.50 per hour. Note that there are also charges for transferring data from an instance to another computer. Step 0: Complete an EC2 Tutorial If you are not already familiar with EC2 instances, you should complete the following tutorial: https://docs.aws.amazon.com/AWSEC2/latest/WindowsGuide/EC2_GetStarted.html Step 1: Create a Security Group You will need to create a security group with the following rules: Allow HTTP traffic on port 80. This allows incoming connections to the FlexSim Webserver. You can choose which inbound IP addresses to accept. You should make this as strict as possible. The strictest setting is to only allow incoming connections from the current IP address. Allow TCP traffic on ports 9000-9200. This is a Custom TCP rule. Note that you can make this range smaller, if all machines that use this Security Group have fewer than 200 cores. For example, if the biggest machine launched with this Security group has 72 cores, you would only need ports 9000-9072 in this rule. Allow RDP traffic on the default RDP port. This allows you to connect to the instance using remote desktop. Name the Security Group something that shows that this group is related to running FlexSim instances, and add a description if you want. Here is an example Security Group that works, but allows all TCP traffic, and so should only be used for testing purposes: Step 2: Create a Custom Amazon Machine Image (AMI) You will need to create a custom AMI. A custom AMI allows you to launch an instance that has the software you need already installed. To create one, follow these steps: Download the FlexSim installer and the Webserver installer. If your upload speed is slow, you can skip this step. Launch the cheapest instance available, with the Windows 2016 Server Base image. There are probably free-tier instances available in the list Connect to that Instance with Remote Desktop Copy (or download, if upload speed is slow) the FlexSim installer to the remote machine, and run it to install FlexSim. You do NOT need to activate a license. Run FlexSim. This creates a directory that is needed later. Then close FlexSim. Copy (or download, if your upload speed is slow) the Webserver installer to the remote machine, and run it to install the webserver. If using the 2018 Update 2 Beta, be sure to change the Webserver configuration file accordingly. Run the Webserver. It will download a bunch of files the first time it is run. Allow both FlexSim and node.js through the Windows Firewall. To do so, use the Allow an App through the Windows Firewall tool. You will need to browse for both FlexSim and Node.js. Both are in the ProgramFiles directory. Disconnect the Remote Desktop session Go to the list of Instances in the AWS Console From the Actions menu, select Image, then select Create Image: Add a name and description. Click the Create Image button On the next dialog, click the View Pending link, or navigate to the list of AMIs: Once the image becomes Available, terminate the running instance. Step 3: Launching Usable Instances Before running an Experiment or Optimization, you need to be sure that all remote instances you will use are current running. To launch and initialize these instances, follow these steps: In the EC2 Console, choose Launch Instance Select the AMI you created, from the list of My AMIs Choose the Instance Type and quantity Set the Security Group to use the Security Group you created Launch the instance Once each instance is initialized, connect to each one with Remote Desktop. Note that when you launch an instance with a given Key File, the password for each instance will be the password associated with that Key File, so you only need to decrypt the file once. Start the FlexSim Webserver in each instance Once all instances are running the Webserver, you are ready to run an Experiment or Optimization. Author's Note: There is probably a way to make it so that when instances start up, they automatically run the Webserver, so that you don't have to manually connect to each one. I welcome any suggestions or steps for how to make that happen. Step 4: Using the Instances in FlexSim Once you have a list of running instances available, you just need to input their IP Addresses into FlexSim, on the Advanced tab of the Experimenter: Once you have input this information, you just need to click the Experiment or Optimize button. FlexSim will then use the remote CPUs for running replications. Considerations Spot Pricing Amazon offers two pricing models: On Demand and Spot Pricing. FlexSim recommends On Demand instances. Spot instances can be significantly cheaper, but they can also be shut down by Amazon and given to an On Demand user at any time, if On Demand requests exceed the number of available machines. FlexSim does not try to recover from this kind of error, and it may lead to unexpected behavior. CPU Count, RAM, and Disk Space When you pick an instance type, be sure to understand how much ram you will need. If a model requires 4 GB of RAM while running, and you use an instance with 128 cores, be sure that the instance has at least 512 GB of RAM, or don't use all 128 cores. Disk space is usually not an issue. However, if you are using the Store Data on Hard Drive option in the Statistics Collector, you will need to be sure that there is enough disk space to run the model to completion on the hard drive, multiplied by the number of cores. The amount of disk space on each instance also affects the total cost of using this service.

A.Hello everyone, Some people we very impressed by FlexSim in a logistics fair and they asked me why are we using Plant Simulation in stead of FlexSim ? I've never heard about this software before, so I had a look on youtube. And to be honest I was impressed by the 3D view and how easy was constructing an automated storage in few seconds without code. I'd like to ask if anybody have used this software ? And what do you think about it ? Thank you very much.

Você tem dúvidas sobre a picklist Values by case? Este Tutorial vai apresentar uma visão geral e fazer um rápido exemplo. Acesse o link : https://youtu.be/d0XVlQlRvmA

O link que segue leva a um vídeo no qual é apresentada uma Visão Geral sobre a ferramenta Script do FlexSim. Os tópicos abordados no vídeo são: O que é o Script? Componentes do Script? Como utilizar o Script? Quais as funcionalidades do Script. Vídeo Tutorial: Script Overview Esperamos que aproveitem mais este vídeo tutorial.

O link que segue leva a um vídeo no qual é apresentada UMA entre várias formas de criar a lógica de alocação de peças no Rack. Os tópicos abordados no vídeo são: Objeto Rack Configurações lógicas do Rack Exemplo prático Vídeo Tutorial: https://youtu.be/tTeRwjt--Eo

O link abaixo, remete a um vídeo onde mostramos como usar o recurso paths para criar o percurso que recursos e pacientes devem seguir durante o fluxo dentro de um hospital, respeitando os limites dos layouts feito em Autocad e, o impacto nos indicadores usando o dashboard para análise. Vídeo Tutorial: FlexSim Healthcare - Parte II Esperamos que aproveitem esses vídeos com algumas dicas simples.