Finding the right answer should be easy. Together we can build and maintain a well organized, growing knowledge base by practicing a bit of good Question and Answer hygiene. Below are 12 tips for using Answers in a way that will help the whole FlexSim community get maximum value from the site, and keep our content organized, efficient, and intuitive. These tips are adapted from this Devada article. Devada makes AnswerHub, which powers this site. Search existing questions before asking. Use the advanced search functionality to look for a question you may have before asking it. You may find your question has already been asked and answered. This saves you and other community members time and effort. Please also search our online user manual. Your answer may be in FlexSim's documentation. Post a model that demonstrates your question. The best case is to make a simple model that demonstrates the question or issue. If the model is sensitive, you can post a private question (see the Private Questions item below for more info). Make your question titles descriptive. Making a question's title descriptive makes it much easier for other people searching the site to find what they need. Question titles like Problem with conveyor are not very helpful when searching, whereas titles like Item gets stuck at photo eye when using area restriction are much more helpful. The question title should not be too verbose, but it should describe the problem well. Post content in the right space. When creating content, it's important to select the appropriate space for it to be posted. Choosing the right space for your content will not only keep the community organized, it's also more likely to be viewed and responded to by the right community members. Need help with some aspect of FlexSim or your simulation? It goes into the Software & Simulation Questions space. Starting a discussion that doesn't have a specific answer? General Discussion is the space it should go in. Don't post an article to ask a question - do that with a question. Don't use a question to request a feature - that should be posted as an idea. Mark correct answers as accepted. It's important to accept a correct answer to a question, especially the questions that you asked. This will make finding the right answer much easier for other members and let the community know that your problem has been solved. Let others know what answers helped you solve questions by upvoting or liking correct answers to show community support. Share your knowledge by answering questions. See a question you know the answer to? Submit an answer with text, images, links, videos, and more to support your answer and to help fellow community members. Use comments and replies. Only post an answer when you're actually answering a question. You can use comments, or directly reply to others' comments to provide support, additional information or ask for further explanations when necessary. Ask experts directly. Want a reliable answer quickly? You can ask an expert directly after creating a question and the expert will be notified. Use the 'at' symbol @ and start typing someone's name, and they will be notified that they were referenced in a post. Be sure to use the autocomplete as you type their name, or you may type it incorrectly and the user will not be notified. A properly formatted @mention automatically becomes a link. If it's not a link (like this: @Ben Wilson!), try again. Avoid overdoing @mentions. Don't make the mistake of @mentioning more people than is necessary to try to draw attention to your question: Your question is just as important as any other question. The community will help you to the best of our ability regardless, so there is no need to spam multiple users in hopes of bumping up your priority. If anything, annoying active members on the community you will only hurt your cause. Monitor reputation points and the leader-board. See how you rank in your community with reputation points. Reputation reflects engagement levels like questions asked, answers submitted, upvotes, and more. Become an expert yourself. Have an area of expertise? By providing knowledgeable answers you can be recognized as a topic expert. The system identifies these users based on the number of accepted answers you provide within a topic. Additionally, you can self-identify areas of expertise in your profile settings. Topic experts receive an elevated role in the community and get notified when content is posted within their area of expertise. Follow topics of interest. Want to continue learning about a specific topic in your community? Follow a topic and receive activity updates in your inbox instantly, daily, or on a weekly basis. Change notification frequency and other settings within your profile. Visit the community often. The more we contribute to the community, the more valuable it becomes for everyone. Have an article you want to share? Post it. Want to share an idea and generate a discussion among other FlexSim users? Answers is a great place to facilitate "ideation" and collaboration. Additional pointers for using answers.flexsim.com: Use the latest version of your internet browser. Mozilla Firefox, Google Chrome, Microsoft Edge, Opera, and other modern browsers should be fully compatible with this Answers site. For the safest, fastest, and most compatible browsing experience, please keep your browser version up-to-date with its latest release. Internet Explorer is an older browser and is not supported. Preparation We expect you to have some foundation of FlexSim knowledge and experience before asking a question. If you're new to FlexSim, before asking questions here, please take the time to go through the in-software tutorials. Topics - when you create a post, whether it's a question, article, or idea, you must tag your post with at least 1 topic (and up to 5 topics) to help identify the main issues of your post. As you add topics, autocomplete will suggest preexisting topics. Please select a preexisting topic if it is a good match, rather than creating a new, slightly different spelling of an existing topic. Also, please try to keep new topics to only 1 or 2 words. Ask one question at a time. When composing a new question, limit yourself to a single question. Don't include multiple questions in one post. Each question deserves its own place. When you separate multiple questions into individual posts, it's more likely that more users will participate in your questions, getting you more answer options more quickly, often from multiple individuals. It also makes each post smaller and easier to digest, encouraging more participation. Follow-up questions. Sometimes it's tempting to ask a follow-up question as a comment to an answer, or even more inappropriately, as a new answer to your first question. New questions that can stand alone should be posted as brand new questions. Only clarifying questions should be asked that expand on the original question/answer/comment that is being discussed. This keeps each question post laser-focused on the top question, and each answer directly pertaining to the main question. An answer should really be an answer. Each answer should directly address the top question in a post. An answer is never a 'thank you', a comment, or another question. Those each have their place (usually as a comment), but none of them should be posted as an answer. A question can have multiple answers. The question asker (or 'OP' - original poster) should 'accept' the answer that worked best for them. Users can up-vote answers that are helpful, or down-vote those that are not. The top answers will bubble up to the top. Conversations go in comments - If you need to clarify a part of someone's question ("what version of the software are you using?"), add a comment to that question. If you want to respond to someone's answer ("thank you!" or "that didn't work for me because..."), add a comment to that answer. Need to respond to someone else's comment? Reply specifically to that comment. Simple and specific questions are best. Simplify your question by creating a sample model that shows the issue, rather than posting a large model (perhaps containing proprietary information) where only one small part of it pertains to the question. Use images to show what is going on and what should be happening. Animated GIFs are even better (example). Public questions are best. They add to the public knowledge base. They will get community participation, and thus get more answers, faster responses, and broader participation. They can help others in the future. Whenever possible, simplify your question for a general audience. Private questions are for private information. If you have a question pertaining to your specific license, make it a private question. Only FlexSim US can see the contents of private questions. AnswerHub takes reasonable measures to help protect information (see their privacy policy's Security heading) but this AnswerHub community should not be considered a secure site. Be sure to follow your organization's rules regarding posting of proprietary data, and when in doubt use approved methods to share confidential information. Consider reaching out directly to your local FlexSim representative for phone or email support. Post attachments: Attachments types - If you find that you can't upload a particular file type, simply compress it to .zip and upload that way. Make a note of that in your post so that we can consider allowing your file type. Attachment sizes - We've tried to be quite generous with total allowable upload sizes. If you find that your attachment(s) are too big to upload, first try compressing to .zip. If that still doesn't get your attachments small enough to post, you may be able to use a 3rd party file hosting service such as Dropbox or SugarSync, and include a link to your uploaded file in your post. Make a note of that in your post so that we can consider increasing the file size limit if this becomes a common problem. Attachment count - Again, we've tried to be quite generous with the total number of attachments that can be added to a post, primarily because images count against your attachment count. Let us know if you're trying to make a post but run into the max attachment limit. Advanced search functions: Simple search A search that uses one or more words, separated by spaces. For example: Enter transporter resource to perform a search for transporter, resource, or transporter resource. Refined search You can refine your search by adding different symbols (+, -, [, or ]) to your search. For example: Entering transporter +resource in the search bar returns results that include transporter and resource, but resource is a required term. Entering transporter -resource in the search bar returns results that include the term transporter, but excludes any that contain the term resource. Entering in the search bar returns only results that are tagged with the transporter topic. Entering [resource] in the search bar returns only results that are tagged with the transporter and resource topics. Google search This Answers community includes Google Custom Search to easily enable the use of Google's powerful search engine across all FlexSim web sites, including this Answers community, our old, archived community, our online user manual, and more. Please see this question and answer for details. If you have any questions, comments, or tips of your own that you'd like to share, please start a discussion in the comments below. We can update the article above with the best suggestions or illuminate anything that might be confusing.

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.

When installing FlexSim, has the installer ever quit, saying "Installation Cancelled" or "FlexSim must close"? Installation Canceled Installation was cancelled by user. Or has your FlexSim installation ever had errors upon starting the software? FlexSim has encountered a problem. Your work is saved in recovery files. Please notify FlexSim Technical Support. Retrieve your recovery files, then email FlexSim. Do you want to restart? FlexSim encountered an unrecoverable error and must close. Please notify FlexSim Technical Support about this issue. This can be frustrating any time, let alone for a brand new FlexSim installation. Here are some possible solutions that may help FlexSim install or start properly: 1. Meet the System Requirements Make sure that your computer meets FlexSim's minimum system requirements. If your computer's hardware or operating system is out of spec, you may not be able to install FlexSim, or it may not start or work properly. Don't overlook the disk space requirement. You'll need about 2.5 GB free for the installer and the completed installation in order to install FlexSim. Low disk space will cause the installation to fail. Graphics specifications are particularly important, as incompatible/nonexistent graphics hardware or out of date graphics drivers may cause strange graphics behavior or other issues. See this article for more graphics considerations, tips, and guidance for installing or upgrading graphics drivers. 2. Windows Updates, Driver Updates FlexSim relies on some newer Windows components and libraries provided by Microsoft in patches and updates. Make sure your computer is up to date with all Windows updates. In addition to Windows updates, be sure to upgrade your system's graphics drivers, as FlexSim relies on fixes and features found in the latest graphics drivers from NVIDIA, Intel, or AMD. It is not enough to just use Windows Update to check for new graphics drivers - you should check the websites for your system manufacturer or graphics vendor specifically for updated graphics drivers. See our graphics article for more detailed information. 3. Reboot your computer Windows has improved enormously over the years, but even with modern Windows sometimes a good, old-fashioned reboot can do the trick, especially if you have recently installed or uninstalled other software or Windows updates. 4. Run as Administrator Software Installation: Ensure that you have the proper privileges on your PC to install new software. Install FlexSim by right-clicking the installer file and choosing Run As Administrator. If you don't have admin rights, you will be prompted to enter credentials with admin rights. Enter the proper credentials to allow the software installation to proceed. Startup Issues: Try starting FlexSim with higher permissions by right-clicking the program icon and choosing Run As Administrator. If you don't have admin rights, you will be prompted to enter credentials with admin rights. Enter the proper credentials and the software should start with elevated permissions. Does this solve the problem? Some users have reported that some FlexSim components are blocked by default, but can run properly when FlexSim is started with elevated privileges. If you find this is the case for you, work with your IT group to determine how to unblock the DLLs or other components required by FlexSim. 5. Delete FlexSim's saved settings Sometimes when FlexSim has trouble starting up, it can be due to a corrupted prefs.t file. FlexSim's prefs.t file stores your FlexSim settings and preferences and is located at: %APPDATA%\Flexsim\FlexSim <version> The %APPDATA% address is a shortcut to your Windows user account's Roaming directory. This animation shows how to get to your %APPDATA% directory: With FlexSim closed, delete this prefs.t file. Then try starting FlexSim. Are the problems resolved? 6. Reinstall FlexSim Completely uninstall FlexSim and try a new installation. It may be worth downloading a new copy of the full installer to ensure there was no corruption in the install package. You could also try the .msi installer, instead of the .exe. When installing using the .msi you can save a log of the install process. This could help with debugging if there are still problems. Whichever method you use when reinstalling FlexSim, be sure to right-click the installer and choose to Run as Administrator (see the Run as Administrator section above). 7. Update your computer's .NET installation FlexSim relies on Microsoft's .NET Framework for some functionality. Windows 10 includes a compatible .NET version, or if a compatible version is missing the FlexSim installer will try to download and install .NET directly from Microsoft. If your computer/network does not allow this you may need to update .NET yourself. Click here to download the .NET framework directly from Microsoft. After installing the .NET Framework, please revisit the Windows Updates section above. Microsoft may provide new security fixes that should be applied to your .NET installation. 8. Reinstall Microsoft Visual C++ Redistributable These are run-time components provided by Microsoft that are required to run FlexSim. Normally these components are installed during FlexSim's installation process. If FlexSim is encountering errors, it could be caused by a broken or out of date C++ redistributable. Click here to download the latest Visual C++ Redistributable directly from Microsoft. After reinstalling the Visual C++ Redistributable, please revisit the Windows Updates section above. There may be new security fixes for the redistributable. 9. Antivirus We have seen instances where FlexSim is blocked by an overzealous Antivirus software. If FlexSim doesn't start up at all, despite a new installation, this could be the case. To test this, temporarily disable your antivirus and try to install or start FlexSim. If the problem clears up then your antivirus may indeed be blocking FlexSim. In this case, work with your IT department to configure the appropriate settings to allow FlexSim to run alongside your antivirus solution. Remember to re-enable your antivirus software after this test. 10. Windows Event Viewer If FlexSim still won't install or start, try checking the Windows Event Viewer to see if there are any errors related to installing or starting FlexSim. If so, please send those our way so that we can troubleshoot further. In case you've never used it before, here is a tutorial covering the Event Viewer. Add your comments below on what did or didn't work for you, other problems or symptoms you encountered, or tips and tricks that helped you solve them. Fixes for older versions The following suggestions apply to outdated versions of FlexSim. Update OpenSSL DLLs Applies to FlexSim versions 7.0.0-20.2.0 (excluding LTS versions 20.0.9+) Some older FlexSim installations may crash shortly after FlexSim opens, when FlexSim's start page contacts our remote servers for dynamic content, due to a new system incompatibility with the openssl library that shipped with these older FlexSim versions. Newer versions of FlexSim include updated files that resolve this problem. Install the latest version of FlexSim to obtain updated versions of the following two files: C:\Program Files\FlexSim <version>\modules\Emulation\openssl\libeay32.dll C:\Program Files\FlexSim <version>\modules\Emulation\openssl\ssleay32.dll Copy those updated DLLs to your affected FlexSim installation, under its program\Webkit folder, overwriting the older version of those files. Alternate workaround: disconnect your computer from the Internet, both wired networks and Wi-Fi. Start FlexSim. Go to File > Global Preferences > Dynamic Content tab. Deactivate all of the options there. You can now reconnect to the Internet and FlexSim may work properly the next time you start the application. Uninstall KB4571756 Applies to FlexSim versions 7.7.0-16.2.2 A Windows 10 patch released in September 2020 may prevent FlexSim versions 7.7.0-16.2.2 from starting. If you are using one of these older versions of FlexSim and the program will not start, try removing this Windows update: https://support.microsoft.com/en-us/help/4571756/windows-10-update-kb4571756

Attached is a sample model that uses Google's OR-Tools python module to find optimal AGV dispatching solutions. I recently stumbled on Google's OR-Tools, which includes several classes for finding optimal solutions to things like vehicle routing, scheduling, bin packing, etc. Since FlexSim now has a mechanism for easy connection to python, I decided to try and see if/how it could be connected to FlexSim for testing AGV dispatching strategies. I threw together this model just to see how/if the connection can work. All source/destination locations are chosen at random, and work inter-arrival rates are random with a user-defined mean inter-arrival time. To get this model running on your side: Install a version of python Run the following from the command-line: python -m pip install ortools In FlexSim, make sure your preferences are configured for the correct version of python, and that python is part of your PATH environment variable. Open the model. In the Parameters table, set DispatchMode to 'VRP Solver'. This model uses the Vehicle Routing Problem solver to find optimal AGV assignment strategies. The main work generation logic is in the 'Work Generation' process flow. At random intervals, work requests arrive. They are assigned to random source and destination locations. Then, when dispatching in 'VRP Solver' mode, the logic calls the optimizeVRP() user command. This command packages the current state of the model into a valid vehicle routing problem, and then passes it to the py_optimizeVRP() user command, which is implemented in python, in the AGVVRP.py file. The command creates the VRP problem using the OR-Tools classes, and then calls the solver, returning the results. OptimizeVRP() then interprets the results and assigns AGVs as needed. Note that the VRP is re-solved every time new work arrives. You'll see little 'freezes' in the execution of the model, because it is solving the VRP at each work arrival. Note that the standard Vehicle Routing Problem is slightly different from the problem this model needs optimized: In an AGV model, there’s no depot. Instead AGVs may be currently located anywhere in the warehouse. There’s no ‘depot-loaded’ capacity of an AGV, and no ‘demand’ at customers. The standard VRP is a situation where trucks are loaded at the depot, and then depleted as they visit each customer in the route. This is not present with single-capacity AGVs. When an AGV picks up at an origin location, it must immediately deliver to the destination location. In order to wrangle the AGV problem into a valid vehicle routing problem that can be solved by OR-Tools, I constructed the problem as follows: I made each AGV’s ‘current location’ a node in the graph The distance from the depot to the AGV’s current location is 0 The distance from the depot to any other node in the graph is prohibitively large. This will cause vehicles to always go to their 'current location' first, with 0 cost. The distance from any node in the graph back to the depot is 0 A given AGV must visit its current location as part of its route. This can be added as a constraint to the problem in OR-Tools For immediate unload after loading, I initially tried adding this rule as a constraint, but the solver hung when solving. So, instead of graph nodes being locations in the facility, I made graph nodes represent ‘tasks’, i.e. visiting this node means picking up the item AND dropping it off. As such, the ‘cost’ of ‘visiting’ a ‘task’ node is the cost to travel from the ‘destination’ of the previous node to the ‘origin’ of this ‘task’ node, plus the cost to travel from the ‘origin’ of this task node to the destination of this ‘task’ node. Once I did this, OR-Tools was able to solve the problem 'optimally'. By optimally, I mean it was finding the AGV routing that minimized the maximum 'travel makespan', which is the maximum distance route of all of the AGVs. Once I had done this, I wanted to compared it with various heuristic-based scenarios. So I set up a 'Closest' dispatch mode. Here, when an AGV finishes a task, it will take up the next task whose pickup point is closest to its current position. I also created a 'FIFO' dispatching mode, which is that work will be dispatched to AGVs always in FIFO order. These three dispatching modes I compared with the experimenter. My initial experiments showed some interesting results. Most interesting was that in 'VRP Solver' mode, work task time-in-system was relatively high. This is because the objective function completely ignored time in system of the work, and was only optimizing for vehicle travel distance. So some work was being pushed off until much later because vehicles could get better travel distances by pushing it off. To account for this, I added a 'soft upper bound', which is kind of like a 'due date' for the work. Namely, work is due to be finished 800 'meters-of-agv-travel' after it arrives. This was a quick-and-dirty workaround and could certainly be improved, but it did serve to get the time in system for VRP Solver mode down. Below are some of the resulting experimenter results. AGVTaskTime - Time from starting a task to finishing it (i.e. a kind of takt time) The VRP solver performed the best across all scenarios here, and was especially better than the other strategies in low-demand scenarios. This intuitively makes sense. When there are a lot of under-utilized AGVs, the closest and FIFO strategies will always dispatch idle AGVs to do work, which could potentially make them travel long distances. However, the VRP solver can find opportunities to decrease travel distance by waiting to dispatch an AGV that will be near a task in the future, and leave other AGVs idle. Note that I think the 'closest' strategy only finds the 'closest' next task for an AGV that just finished a task, not the 'closest' idle AGV for an arriving task. Obviously that could be changed for a better performing 'closest' strategy. On the other hand, I think in this model all idle AGVs go back to the same park location, so such a change would require distributed park locations to take advantage of closer idle AGVs. AGVWorkStaytime - time-in-system for a given AGV task Here the 'closest' strategy actually performed better than the VRP. This would seem counter-intuitive at first, but upon further evaluation, it does make sense. The VRP, in its current form, only optimizes for total AGV travel distance. It completely ignores job time in system/due dates/etc. So the solver will always assign a route that is shorter even if that route pushes back jobs that have been in the queue for a long time. The solver also re-solves every time a new job arrives. So we may be having scenarios where some jobs are always 'better' to be pushed to the end of the route, and so they keep getting pushed back, resulting in poor time-in-system performance. The solver does include soft and hard job 'due dates', so we could make adjustments to the problem to make the VRP get better time-in-system results. AvgAGVUtilization AvgAGVUtilization is where the VRP especially shines in low-demand scenarios. It finds opportunities to leave AGVs parked because there will be opportunities for busy AGVs to take up jobs in the future with minimal extra travel overhead, whereas the 'FIFO' and 'Closest' strategies will always dispatch idle AGVs to unassigned jobs, causing extra unnecessary empty travel. I am still a bit perplexed by the high-demand scenarios though. Here the 'Closest' and 'FIFO' strategies both beat the VRP in the 120/hr and 102/hr scenarios. This probably would warrant further investigation as to why the other strategies do better here. It may be that, in these scenarios, the AGVs cannot keep up with demand. So there is a queue of jobs that is ever-increasing. The VRP solver is optimizing the full plan, meaning it is scheduling job assignments, and finding travel distance minimization opportunities, that are way out into the future. And it is not getting the opportunity to execute those optimized routes because the problem is being re-solved at each job arrival. With an increasing job queue, the 'closest' and 'fifo' strategies might be actually doing better specifically because they are short-sighted. Just take the closest job to you. On the other hand, if we have increasing job queues (i.e. the AGVs can't keep up), then the AGV utilization should be around 100% anyway, which it's not. Anyway, it's something still to churn on. ThroughputPerHour The throughput per hour indicator tells us whether the AGVs actually kept up with the jobs. If the AGVs were able to keep up with jobs, then the resulting means should be right around the scenario's throughput/hr number. It looks like FIFO got way behind on both the 120/hr and 102/hr scenarios. 'Closest' and VRP both got a little behind in the 120/hr scenarios. One exciting possibility of using this design is that the python script is not technically dependent on FlexSim. So you can use FlexSim to test your python-based optimization, and then you can deploy that python script in a live setting. AGVVehicleRoutingProblem.zip

Article space for Production Engineer Book including FlexSim Examples from Brasil Este material de apoio faz parte do Livro Administração de produção e operações, manufatura e serviços: uma abordagem estratégica, dos autores Henrique Correa e Carlos Correa, em sua 5º Edição. Para auxiliar o aprendizado, este livro conta com exemplos em vídeo e modelos de simulações de processos disponíveis em diversos capítulos. O acesso ao material é gratuito e pode ser acessado através dos links abaixo nas descrições de cada capítulo. Aqui você encontrará o conteúdo detalhado, referente aos arquivos dos modelos de simulação (*.fsm) e os links dos vídeos no YouTube. Dessa forma, o leitor poderá usufruir dos arquivos de simulação criados para facilitar e enriquecer o seu aprendizado. Capítulo 10 Projeto do Produto e Seleção de Processos (Bens e Serviços) Call Center download modelo clique para assistir o vídeo Restaurante download modelo clique para assistir o vídeo Clínica download modelo clique para assistir o vídeo Loja de conveniência download modelo clique para assistir o vídeo Segurança de um aeroporto download modelo clique para assistir o vídeo Terminal Rodoviário download modelo clique para assistir o vídeo Hospital clique para assistir o vídeo Estacionamento clique para assistir o vídeo Capítulo 13 Localização e Arranjo Físico de Unidades da Rede de Operações Layout Celular clique para assistir o vídeo Layout em Linha clique para assistir o vídeo Layout por Processos (em breve) Layout Posicional (em breve) Capítulo 14 Capacidade Produtiva e Filas em Unidades da Rede de Operações Teoria das Filas download modelo clique aqui para assistir o vídeo Capítulo 15 Teoria das Restrições em Redes de Operações TOC Princípios 1-9 download modelo princípio 1 download modelo princípio 2 download modelo princípio 3 download modelo princípios 4 e 5 download modelo princípio 6 download modelo princípio 7 download modelo princípio 8 download modelo princípio 9 clique para assistir o vídeo Sistema Drum-Buffer-Rope (Tambor-Pulmão-Corda) download modelo clique para assistir o vídeo Capítulo 17 Gestão de Estoques na Rede de Operações Simulação de Reposição Periódica / Contínua (em breve) Capítulo 19 Sequenciamento, Programação e Controle de Operações Sequenciamento de Produtos e Otimização download modelo clique para assistir o vídeo Job-Shop download modelo clique para assistir o vídeo Capítulo 20 Just in Time (JIT) e Operações Enxutas (Lean) Produção Puxada vs. Empurrada download modelo clique aqui para assistir o vídeo Cartão Kanban Assista o vídeo e veja na prática um exemplo de simulação do sistema kanban. download modelo clique aqui para assistir o vídeo Desperdícios do Sistema Toyota de Podução (Lean) download modelo clique aqui para assistir o vídeo Setup Assista o vídeo da simulação de um processo de troca de piso da quadra de uma arena multiuso, utilizada para partidas de hóquei e de basquete. clique aqui para assistir o vídeo Informações Adicionais Os modelos de simulações e os vídeos apresentados foram construídos com o Software FlexSim, plataforma digital, a qual possui uma versão gratuita, FlexSim Express, disponível para download através da URL https://www.flexsim.com/pt/ Vídeo passo a passo download e instalação do FlexSim Express Vídeo requisitos de sistema hardware para utilizar o FlexSim Express Contatos suporte@flexsimbrasil.com.br / @Rodrigo Lamas / @Michael Machado

Recommended System Requirements This article complements FlexSim's System Requirements. We'll go over each of the major components, discuss their importance to a FlexSim model, and make recommendations to help you decide on the right hardware for your situation. CPU Single Model Run A single run of a FlexSim model (ie not an experiment or optimization run) is single threaded, which means it runs on only 1 CPU core. Buying a processor with more cores won't speed up a single simulation run. To complete single model runs more quickly, use instead a processor with a faster single core clock speed (gigahertz, or cycles per second) or better efficiency (instructions per cycle). In short, for the fastest individual model runs, you want the fastest processor possible, regardless of the number of cores. Experimenter or Optimizer - Multiple Simultaneous Replications When you're doing multiple simultaneous model runs using the Experimenter or Optimizer, FlexSim takes advantage of multiple CPU cores to run simulation replications in parallel. By default, FlexSim spawns as many replications as you have cores; for example, a Quad core processor enables four single-threaded simulation runs to process simultaneously, one on each core, getting you results four times faster than by using a single core processor at the same speed/efficiency. If necessary, you can manually limit the number of concurrent replications by setting the Max Cores value from FlexSim's Main Menu under Statistics > Experimenter > Advanced tab > Max Cores input field. Each replication consumes some amount of system RAM, so if you run out of RAM before you run out of cores, it may be necessary to limit the number of cores used to run replications. Conclusion If you’re primarily doing single simulation runs, choose a faster processor speed regardless of the number of cores. If you’re primarily doing experiments, choose a processor with a high number of processing cores (and make sure your system has enough RAM to support them - see Memory below). If you’ll be doing both, choose a processor that strikes a good balance between core speed and core count. Memory Considerations Random Access Memory, or RAM, is a PC's fast "working" memory, where it stores the data and programs it is currently running (don't confuse this with your much slower hard drive, where data is stored "at rest"). Most consumer Windows computers top out at 32 or 64 GB of RAM, though Windows is capable of supporting much more when coupled with high-end hardware (see limits per OS here). Your computer is always doing many other things besides just running FlexSim. Your operating system itself has memory needs for all the processes it is constantly running. You probably have an antivirus solution, maybe a backup software, and often other utilities running invisibly in the background. Then there are all the applications you currently have open - your email, a web browser, music streaming, etc. All of these are consuming RAM. As you plan your FlexSim hardware, be aware that you should have enough RAM to run all these other applications, plus your FlexSim model, plus have a good amount of extra RAM as a buffer. FlexSim's Requirements Many FlexSim models will use less than 4 GB of RAM in a single model run, but it all depends on your simulation and data. Some large and complex models can and do go above 4 GB of RAM utilization (sometimes well above). If FlexSim's RAM utilization starts approaching a high percentage of your total available system RAM, your computer will turn sluggish or totally unresponsive as it runs out of memory and begins paging out to disk for its memory needs (which is orders of magnitude slower than RAM). A FlexSim system should have 8 GB of RAM as a minimum. For the best experience we recommend 32 GB of RAM or more. Many modern high-end consumer PCs meet this recommendation. See FlexSim's latest minimum and recommended system requirements here. Experiments and Optimizations Experiments and optimizations run several replications of your model simultaneously, so make sure you have enough total memory in your system so that each replication can hit its peak memory needs, while still leaving enough memory for the system and other running applications (OS, antivirus, other background processes, etc.). In addition, the experimenter saves statistics data for each replication by default. Each completed replication will send its statistics collectors' data to the main FlexSim thread, where it will ultimately be stored in the results database file on the hard drive. However, several stages of the transfer process require two copies of the data. In addition, all child processes can transfer data simultaneously. So, if you have a model that generates 100MB of statistics data, and you run an experiment with 8 CPUs, and all 8 CPUs finish a replication at roughly the same time, you'll need at least 1600MB (100 MB x 2 x 8) to transfer the data successfully, on top of all the other RAM utilization. Example Scenario I've developed a simulation model and now I'd like to run multiple replications using the Experimenter. Watching my simulation run normally, while monitoring FlexSim's memory usage with Windows Task Manager, I see that over the entire course of its run my simulation peaks at about 2.1 GB of RAM at its highest utilization. My computer system has 16 GB of RAM. When FlexSim is not running at all, the system uses about 20% of its resources for the operating system and other background processes. This leaves about 12.8 GB of RAM free. How many concurrent replications of FlexSim can my PC support? 12.8 GB / 2.1 GB per replication = 6.1 concurrent replications So, I might get by with allowing 6 concurrent replications of FlexSim, but I feel like 5 is a safer bet to give the system a bit of headroom, and because running the experimenter and collecting results data also requires some additional memory overhead. Since my computer has a quad-core processor and uses simultaneous multithreading (SMT) (which allows each core to run two FlexSim replications at once), FlexSim's default would be to run 8 concurrent replications. My calculations showed that 8 concurrent replications would be too many, and will probably bog down my PC, slowing or halting the entire process. I will limit the number of concurrent replications the experimenter will use by setting the Max Cores value to 5. This option is set from FlexSim's Main Menu under Statistics > Experimenter > Advanced tab > Max Cores input field. Your settings will differ from this example. Check your computer's amount of RAM, the peak memory needs of your simulation models, and your baseline RAM utilization when you're not running any simulations. Factor in a reasonable % as a buffer. Use these values to determine how many concurrent FlexSim replications your computer may support. When allowing FlexSim to use its default of running the max number of replications your CPU supports, please keep in mind that many multi-core CPUs actually run multiple threads simultaneously per core (simultaneous multithreading - SMT). To fully take advantage of all the simultaneous replications that your PC could run at once, be sure to get enough RAM for all the replications your CPU is capable of. For example, a 4-core CPU with support for SMT could run 8 simulation replications at once. Make sure you have the memory to do so! If not, be sure to use the Max Cores option to limit the number of concurrent replications. Conclusion A system meeting FlexSim's minimum RAM requirement will have enough memory for a single model run of most simulation models. If your simulations are large or complex, or if you intend on running experiments or using the optimizer, you should meet the higher recommended spec of 32 GB of RAM or more. Disk Space Requirements The FlexSim installer may be up to 1.2GB in size, depending on the FlexSim version. After installation, FlexSim's program files use up to 1.2GB of disk space. Your model files, CAD layouts, images, custom 3D shapes, import data, exported reports, and other simulation related assets that you provide will take disk space in addition to the software's installation footprint. Disk Speed Most FlexSim models will run from memory, so hard drive speed isn't really an issue. However, if you're reading/writing with files/databases while the model is running, disk speed could make a huge difference; a Solid-State Drive (SSD) is a must in that case. Alternatively, try to do data reading and writing before and after the simulation run, if possible. FlexSim recommends SSDs in general because they make every interaction with your computer feel faster and more responsive. You won't regret an upgrade from a regular, spinning hard drive to an SSD. Conclusion Consider upgrading your hard drive to an SSD if you will be reading or writing to files or databases during a model run, or to generally improve system responsiveness. Graphics Recommended Graphics The better/newer/bigger/faster the graphics processor, the better the performance. Integrated graphics, where a smaller GPU is packaged into the CPU, have gotten much better in recent years, but a discrete GPU remains the most powerful graphics solution. FlexSim works best on Nvidia GeForce RTX or GTX GPUs, but Nvidia Quadro and AMD Radeon are also good solutions. Most recent integrated graphics solutions meet FlexSim's minimum graphics requirements, but in general will not perform as well as discrete graphics. Graphics Driver Updates It is also important to note that you should keep your graphics drivers updated to the latest version. If your graphics hardware meets FlexSim's minimum requirements but you are experiencing graphical issues in FlexSim, a graphics driver update may solve the problem. Please check out this article for some common symptoms and solutions to graphics issues within FlexSim. Virtual Reality FlexSim supports Oculus Rift/Meta Quest 2, HTC Vive, and Windows mixed reality virtual reality platforms (see demo models). Be sure to meet FlexSim's higher recommended specifications if you plan to use VR. Conclusion While recent integrated graphics solutions meet FlexSim's minimum requirements, a discrete graphics solution is a better choice. For maximum performance, FlexSim recommends a recent NVIDIA GeForce RTX GPU.

FlexSim requires modern graphics support to run well. Most modern computers from the last few years have no problem running most FlexSim models, but sometimes there are graphics configuration issues that keep FlexSim from working properly. Common symptoms The model 3D view is black or blank. You should see the model view default to a 3D grid. The 3D grid appears, but does not respond to user interaction. You should be able to click and drag the grid to pan (left-click-drag) and rotate (right-click-drag) the view. Click the grid to select it then scroll your mouse wheel - this should zoom the 3D view in and out. Unable to drag an object onto the grid. You should be able to click and drag an object from the Library and drop it onto the 3D grid. It should appear at the location of your mouse. Unable to interact with objects in the 3D view. You should be able to double-click an object to bring up its properties window, or single click to highlight, or click and drag to move it about the 3D grid. Conveyors or other objects are not drawing to the view. Unable to create connections between objects. User interface elements and other GUIs are not displaying correctly. Solutions If you are experiencing any of these issues, it is most likely a graphics compatibility issue. Here are common steps you can take to solve the problem: Open FlexSim's default workspace to reset any potentially corrupted view windows. To do so, from FlexSim's main menu, go to View > Open Default Workspace. Any open windows will be closed and the default 3D view and tool panels will be opened. This could clear up potential issues with 3D or Process Flow views, tools panels, or properties windows. Check that your computer meets FlexSim's minimum system requirements. Review FlexSim's minimum and recommended system requirements. Check this article for an in-depth explanation of hardware considerations. Update your graphics driver to the latest version. This almost always solves graphics issues and is the preferred solution whenever possible. It enables the maximum performance from your graphics hardware and eliminates bugs and glitches in previous drivers. Check out HowToGeek.com's article for a primer on updating graphics drivers. Always go directly to your graphics manufacturers website ( Intel, AMD, or Nvidia) to get the latest drivers for your graphics hardware. Do not trust that Windows Update always gives the latest graphics drivers - in fact it rarely does. Not every user has the proper administrator privileges on their computer necessary to update drivers, so you may need to contact someone in your IT department for help. Try a different graphics driver. If the graphics aren't working correctly and you downloaded the latest driver for your hardware directly from Intel, AMD, or Nvidia, try instead using the latest driver from the computer manufacturer such as HP/Dell/Lenovo/Asus/Acer, etc. If you are already using the latest driver from your computer manufacturer, try using the latest driver from the graphics card manufacturer: Intel, AMD, or Nvidia. Try starting FlexSim with higher permissions by right-clicking the program icon and choosing Run As Administrator. If you don't have admin rights, you will be prompted to enter credentials with admin rights. Enter the proper credentials and the software should start with elevated permissions. Does this solve the problem? Some users have reported certain linked libraries used by FlexSim are blocked by default, but can run properly when FlexSim is started with elevated privileges. If you find this is the case for you, work with your IT group to determine how to unblock the DLLs required by FlexSim. Try turning off Shadows by going to File > Global Preferences > Graphics tab, and uncheck the option Use Shadows. Click the Apply button, then close. Restart FlexSim to see how it responds with this changed setting. Try switching to a different OpenGL Context by going to File > Global Preferences > Graphics tab, and make a new selection for OpenGL Context. Hit Apply, then close. Restart FlexSim and see how it responds. Start with Recommended, then try Core Profile (3.3). If Core Profile (3.3) still doesn't work, try Generic. The Generic context is the last resort option, and is equivalent to the Compatibility mode option in versions of FlexSim previous to 2017. Compatibility mode/Generic Context is not intended for long term use. Revert to this mode only if you must use a computer that doesn't meet FlexSim's minimum system requirements. Test with other 3D applications. Your computer hardware or operating system may have an underlying problem that is causing your graphics issue. You may be able to test this by starting different 3D-accelerated applications or games on your computer. Do other applications besides FlexSim have graphics issues? If so, and you have already tried upgrading your graphics drivers as described above, you may need to contact your IT department or your computer's manufacturer for support. You may have hardware or other issues that prevent your 3D graphics from working properly. Contact FlexSim to let us know that your computer meets FlexSim's minimum system requirements you have installed the latest drivers for your graphics card other 3D-accelerated applications on your computer work just fine but your FlexSim installation still has graphics issues. If this is the case, there may be a software problem in FlexSim that should be addressed. When contacting us about your graphics problem, please include the following: Describe your symptoms in detail. Screenshots are very helpful. For each of the troubleshooting suggestions above, what did you try? What was the result? Please include a screenshot of your FlexSim installation's About FlexSim popup (from FlexSim's main menu > Help > About FlexSim...). This gives us info about your FlexSim version, your graphics hardware, and your graphics driver: A screenshot of your Windows Device Manager, with Display Adapters expanded, is also helpful for our troubleshooting. This gives us additional information about your graphics hardware: Special Cases Nvidia Quadro cards have many different driver versions. We have had good success using the ODE driver (‘Optimal Drivers for Enterprise’). Another option that sometimes improves Quadro compatibility with FlexSim is to open your Nvidia Control Panel and change 3D settings to "3D App - Game Development": Your laptop may have both Intel Integrated graphics and Nvidia/AMD accelerated graphics, and the ability to automatically switch between them depending on the application's 3D requirements. This is a great feature and helps to maximize your battery life. FlexSim should be automatically recognized as a program that should use discrete graphics acceleration, but in case it is not, you may need to set it manually within the Nvidia or AMD Control Panel. Here is the Nvidia Control panel. You can specify an acceleration profile for FlexSim under 3D Settings, Manage 3D settings, Program Settings tab: Click 'Add' and browse to the flexsim.exe executable (default install path is C:\Program Files\FlexSim <version>\program\flexsim.exe). You then have the ability to tweak any and all settings for your FlexSim graphics. The defaults are usually fine, but feel free to play around to tweak things to your liking.

Requirements FlexSim 25.0 or later (found in the downloads page) NVIDIA's Omniverse USD Composer Background Historically, users have used USD Stages in FlexSim to create a live connection with an Omniverse application to be able to simulate animations in Omniverse. However, this relies on a live connection between FlexSim and Omniverse. Sometimes this type of connection is sub-optimal for a user's situation. This article will explain a workflow for writing animation data to a USD file to play in an Omniverse application independent from FlexSim. Disclaimer All the data we record during this example is meant to help us write meaningful data into a .usd file so we can generate an animation in USD Composer. When I say "animation", I mean positional and rotational data along with showing/hiding flowitems. If you want to see Operator Skeletal Animations, I'll post a similar article with a few tweaks later to showcase how to do that using USD Composer's Sequencer, which uses Tracks and Asset Clips to handle small-scale skeletal animations. Example Model I've built a sample model demonstrating the changes to the USD API and how to use them. This example model is just one way to use the API -- there are other ways that users are free to explore. example_model.zip Explaining the Model When you open the model, you'll see a few different windowpanes. In the top-right corner, you'll see a Global Table. If you reset the model, you'll see column headings appear. Each column is a different piece of data we'll be writing to the USD Stage. Each row is a different entry of data to write. In the center views, you'll have a 3D view on the left side and a Process Flow (PF) on the right. At the bottom, there's a script window with a few lines of code. Those lines of code are User Commands I defined to summarize the functionality they encapsulate. The 3D View In the 3D view, you should see some queues, processors, operators, and conveyors. This is a simple workflow where items come into the queues, operators move them into the processors for processing, and then the operators send them down the conveyor lines. With this model, we'll demonstrate (1) operator movement and (2) flowitem movement on conveyors. Setting Up the USD Stage There should be a "USD Stage1" present in the model. If you click on the USD Stage, its properties will appear on the right-side of the screen. In it, you'll see a blank edit field. This is where you put the path to the USD file you want to work on have appear. If you want to save a fresh one, while the edit field is blank, click the "Save" icon next to it. Once you select where you want to place the file, name it, and close the file explorer popup, the edit field should populate with the full path to the .usd file. For more info, you can check out the docs page on the USD Stage object. Viewing the Model in USD Composer Once you've saved your USD Stage, you can open the .usd file in any software that can view .usd files. For this demonstration, we'll be using NVIDIA's Omniverse application which as a USD Composer module. The Process Flow Open up the Process Flow tab to view the simple setup. I'll walk through each part of the PF to give you an idea of how it works. Operator Movement This block of PF is in charge of recording information about Operator positions and rotations. It records information whenever an Operator starts and ends a task. You can expound on this concept and record information when specific triggers or events happen, but for this example I kept it simple and record when any task happens. User Command: RecordInfoToTable Within the "Record Info" Activity, it calls a User Command to record information to the table. This function simply takes a token as the first parameter. This is what the code looks like: Token token = param(1); // Setup row for this iteration Table animInfo = Table("AnimationInfo"); animInfo.addRow(); int curRow = animInfo.numRows; token.labels.assert("Row", 1).value = curRow; animInfo[curRow]["Object"] = token.operator; animInfo[curRow]["AnimTime"] = Model.time; animInfo[curRow]["TaskType"] = token.taskType; // Record positional and rotational data Object operator = token.operator.as(Object); animInfo[curRow]["PosX"] = operator.location.x; animInfo[curRow]["PosY"] = operator.location.y; animInfo[curRow]["PosZ"] = operator.location.z; double Z = Math.fmod(operator.rotation.z, 360); if (Z < 0) Z += 360; animInfo[curRow]["RotX"] = operator.rotation.x; animInfo[curRow]["RotY"] = operator.rotation.y; animInfo[curRow]["RotZ"] = Z; To summarize: Start by assigning the value of the token (parameter 1) to the local variable "token" We get a reference to the Global Table (AnimationInfo) and add a row for the data we're about to write Record (1) which operator this data is for, (2) what time this is happening, (3) and the type of task they're performing. The task type isn't as important - it's for finer details and debugging if necessary. Then we record the positional data of the operator. We previously saved the "operator" label onto the token, so we can use that and "cast" it to be an Object. We do this because the Object class has a "location" property which holds the x, y, z coordinates of the object. Lastly, we do the same thing with "rotation", except we need to bound the rotation to be a positive number between 0 and 360. To do this, we call Math.fmod() to get the reminder after dividing by 360. If the value is negative, we add 360 to get a positive value. Running the Model If you reset and run the model to the stop time at 200, you'll see the Global Table populate with data. There should be valid data for all the columns except the last 3. The "BoxNum", "EntryConveyor", and "Show" columns are for recording flowitem data. We'll discuss that later. Once you've got data in the table, we can run the User Commands in the script window at the bottom of the screen. They should be: ClearTimestampedData(); return WriteToUsd(); The first one "ClearTimestampedData()" is used to loop through the operators and clear all their time-sampled data. We do this so no old data is used if you change things in the FlexSim model and export new data. The second one "WriteToUsd()" is what reads the Global Table line by line, defines and finds prims, writes time-sampled data to them, and saves the information to the .usd file. View the Animation in USD Composer After running these scripts, you should get a prompt in USD Composer to "Fetch Changes". Fetch the changes. Then, open the Timeline feature (Window > Animation > Timeline). This opens an animation timeline at the bottom of the screen. You can save predefined start and end times for the whole stage using the Flexscript API if you choose. Otherwise, you can change the settings manually in USD Composer. (I've color-coded the image below to help explain the tool.) On the far-left (green circle) is the starting frame of the animation while the far-right (red circle) is the ending frame. The inner numbers allow you to set specific sections of the animation to play. If not set, it will play the whole animation. The top-right value and blue "scrubber" (blue circle and arrow) denote the current frame. When you hit your space-bar (or click the "Play" button), that scrubber should move. The value next to FPS (yellow circle) represents the "Frames per Second" the animation runs at. If you want it to play faster, then you can set it to a higher FPS. Note that this example model is built assuming 24 FPS. There is a User Command "TimeToFPS" that simply multiples the given Model time by a desired FPS, defaulting to 24 FPS. If you want to change that rate, you can set it in the code. Now that we've got the animation timeline setup, hit play and watch the animation. You may need to adjust the animation range to be 850 to 4800 so you can see the movements. Like I mentioned in the Disclaimer, if you want to see skeletal animations in the Operator, I'll have another article explaining how to add that functionality. Add Flowitem Movement on the Conveyor Let's go back to FlexSim and check out the Process Flow again. I have two other containers labeled "Box Movement: Time-based" and "Box Movement: DPs". These flows represent two different ways to record this data: either based on a time interval or based on Decision Point positions. The time-based way can be more accurate, but it adds much more time-sample data than the DP version. Choose one of the versions to test out, open the properties of their Source, and then Enable it. If you reset and run the model, you'll start seeing entries for Flowitems. They'll utilize the last 3 columns of the Global Table to keep track of (1) the Box# they are, (2) the Conveyor they entered on, and (3) whether or not to "show" their prim. Click here to learn more about prim visibility. Run the scripts to export and save the model. Then, fetch and view the changes in USD Composer. Conclusion We've covered how to use some of the new features of the USD API in FlexSim 25.0 to create stand-alone animations in .usd files. We used FlexSim to record and export data to .usd files to then display in USD Composer. You can now play a standalone animation in USD Composer without a live connection to FlexSim.

Intersection with traffic lights in an AGV network This model aims to showcase how allocations of control areas can be manually controlled to achieve more complex logic than the default “first come first serve” implementation. It depicts a four-way road intersection with arriving cars being able to continue in any of the three other directions. Cars driving straight on or turning right use the right lane, cars turning left use the left lane and must give way to oncoming traffic. Traffic lights manage which cars are allowed to enter the intersection at any given time. AGV network and general concept In order to understand the logic behind it, let’s first look at how the AGV network is setup. In the screenshot below we deactivated the visualization of the roads to show the paths and areas more clearly. For each of the four directions there are two incoming paths and one outgoing path. Control points (red) are placed on the incoming paths at the points where cars must stop (based on object center) when the light is red. A single, large control area that control the entry is placed such that is encompasses the entire intersection. Within this control area, an additional control point is placed on each of the left turning paths (orange). This is the location where left turning vehicles must wait for the oncoming lane to be clear. To enforce this the four smaller, rectangular control areas are used. The lane turning left and both the straight and right turning lane coming from the other direction pass through one of these areas. We will later explain how the straight and right turning cars are given priority to allocate these areas, resulting in cars wanting to turn left having to wait until no other allocation requests are present. As all paths are one-way and the geometry is pretty simple, all things considered, the distance between cars is handled by an accumulation behaviour set on the paths. The logic controlling the vehicles is very simple. If we zoom out, we can see that cars leaving the intersection in any direction eventually just turn around and return. At the turning points control points are placed that serve as the travel destination for the cars. A Process Flow with one token per car randomly chooses the next destination when the previous travel task is finished and sends the car there. The cars will automatically use the correct lanes, since those are the shortest paths to reach their destination. For the intersection logic each combination of origin and destination (meaning every possible way of crossing the intersection) is represented as a number. These numbers are stored as global macros for ease of use. The letters represent the four cardinal directions (north, west, south, east). For example, using the intersection to travel from east to west would be represented by the ‘mode’ number 4. At the same time as a new destination is chosen for the car, the respective mode number is also written to a label on the car. In the logic that controls entries into the intersection, these modes are used to identify which vehicles are allowed to enter. Powers of two are used, so the numbers can simply be added together to get a single number that encodes which lights are green. The light phases are defined in a global table. One of the simplest sensible configurations is shown below. At first, all lights are red (no entries in the “Green” columns) for 5 seconds. Then all cars coming from the west and east directions receive a green light for 20 seconds. This is followed by another 5s of all red lights and finally the other directions are allowed to move on. The table is then repeated from the top. The phase in line two would be represented as mode 1365 (1 + 4 + 16 + 64 + 256 + 1024). This becomes a lot more obvious when the mode is written in binary: 0000 0101 0101 0101 Each bit represents one of the possible directions. Allocation logic explained The control area is set to allow 0 concurrent allocations. Meaning for a request to actually result in an allocation, we need to override the return value of the “On Request” event of the control area. This happens in the control logic for the intersection that is implemented as an Object Process Flow linked to the control area. An Event-Triggered Source reacts to the On Request event and writes a reference to the “Allocator” (meaning the car/AGV) to a label on the token. Note that the “Will Override Return Value” box is checked. The token then enters a Finish activity in whose “Return Value” field the current traffic mode of the control area is compared to the mode of the requesting car. The “&” is the bitwise-and-operator. It goes through both numbers bit by bit. If the bit at a given position is 1 in both numbers, it will also be 1 in the returned value, 0 otherwise. If the mode of the car is part of the current traffic mode (which is a sum of such modes) the result will be the mode. This non-zero number is interpreted as “true” in the if-condition and the return value of the code is to allow the request to go through. Otherwise, the request is blocked. (The “Allow” and “Block” properties return 1 and -1, respectively.) The second part of the Process Flow is a loop with a single token that reads the next traffic mode from the global table. It then ‘announces’ which phase the intersection will enter next, so that the draw logic of the traffic light objects can start the process of switching from red to green or vice versa if needed. After a delay, in which those lights would show yellow, the current phase of the control area is updated. The same code that updates the label then also searches for cars that are now allowed to enter the intersection among the pending allocation requests. Since, as far as I could tell, there is currently no direct method to refire an allocation request, those cars receive a pre-empting task sequence that uses a break task to immediately return to the previously active sequence. The restart of their travel task then causes them to try to allocate the control area again. After waiting the duration assigned to the current traffic phase, the token once more updates the mode of the intersection to an ‘intermediate’ mode. This mode is the result of another bit-wise comparison of the current and the next mode. This allows lights that need to change to red to do so, while lights that stay green remain unchanged. Once the next phase is activated, additional lights might then become green. If the next phase doesn’t have any green lights, all lights will already be red in the intermediate mode, meaning the Process Flow block that updates the mode can be skipped and the token instead just waits out the duration in the “All Red Duration” Delay activity. The logic that makes left turning vehicles give way to oncoming traffic works in a similar way. It is also implemented as an Object Process Flow, linked to the four smaller control areas within the intersection. These areas allow a single allocation by default and also have a “Mode” label. But it’s not set based on a timer and otherwise static. Instead, these areas start in mode 0 and if a request is made while the area is empty, the allocation is always allowed, and the mode is set to match that of the allocator. When another request is made, the areas mode is compared with that of the new requesting car. If they match, the request can potentially be granted. First however, the code searches other pending requests for a mode with a higher priority than that of the current request. (The mode numbers are assigned in the order straight < right turn < left turn, so they can also be used as a priority value, where lower is better.) If such a request is found, the current one is blocked, to allow for the area to empty. At that point, a token created by a source listening to the “On Deallocated” event of the control area will reset the mode of the area to 0 and sort any pending requests by priority, before those get re-evaluated. In summary, this logic allows an arbitrary number of cars with the same mode to enter the area. As soon as a higher priority request that can’t immediately enter is created, other requests are blocked; they must ‘give way’. Visualization and parameters The traffic lights are BasicFR objects that draw colored circles as lights in their On Draw trigger, depending on a label. That label is updated in the On Message trigger whenever the intersection changes its phase. The roads are drawn along the AGV paths in the On Draw code of a dummy object placed to the side of the intersection. How wide and in what interval the white lines are drawn is determined by Array labels on the paths containing all necessary parameters. The model comes with five parameters: The first controls which table is used to determine the traffic light phases, the second and third set the time it takes a light to switch from red to green and green to red. The fourth sets the number of cars and the final one switches the visualization of the left turn lights to arrows. agv-traffic-mode-intersection.fsm

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.

The ideal way to access the User Manual is by viewing an electronic copy either online or inside the software. Online User Manual The User Manual is available online at docs.flexsim.com. There you can select a software version and manual language. We hope to provide additional languages in the future. In-software User Manual There are two ways to open the manual inside FlexSim: Click the User Manual button on the main toolbar. Click the Help menu and then click User Manual. Why the electronic manual is preferred The online / in-software version of the User Manual is better than a print or PDF version for many reasons, including: Regular updates - The electronic version keeps up with every new FlexSim release. A printed manual unfortunately goes out of date every four months with each new release of FlexSim. The online manual allows you to also view older versions of the manual. Animated GIFs - Animations enhance communication by making it possible to see FlexSim in real time. Animated GIFs won't work in a printed copy. Better search - The online version allows you to search the manual using Google. The in-software version also has a search program which is easier than trying to find relevant keywords within a large document. Styled and reflowable tables, images, and tip boxes - While these elements look good on the web, print or PDF versions don't always correctly format their placement within the document. Better organization - A printed manual won’t always maintain the same organization as the online and in-software manual, making it more difficult to navigate. Mini-table of contents - Each topic has easy navigation within each topic via inner-links. A printed or PDF mini-table of contents (found in most topics) can't function as a clickable index, making it difficult to easily skip to relevant sections within a topic. Printing topics from the User Manual While we don't recommend printing the entire manual, you can easily print individual topics for later reference. Print from the online manual Visit docs.flexsim.com using your favorite modern web browser. Use the table of contents in the left navigation bar to visit the topic you want to print. Use the printer button in the upper right of the topic window to print the page: Print from the in-software manual In FlexSim, open the User Manual and browse to the topic you'd like to print. Press the 'world' button to open the topic in your web browser. Choose the print function inside your web browser - depending on your browser, you may be able to right-click the web page and choose Print, or you can use the keyboard combo Ctrl+P.

Introduction Several times per year we release a new feature-version of FlexSim Simulation Software. In order for your PCs to be able to run a licensed version of the upgraded software, you'll need to upgrade your standalone FlexSim license. Licenses with a current maintenance subscription are eligible to be upgraded to the new version. If you don't understand how licensing works for different FlexSim versions, please review our Answers article FlexSim Version Numbering. Overview After installing your new version of FlexSim, there are 3 main steps to upgrading your standalone license: Return the licenses you intend to upgrade Upgrade your licenses Activate the upgraded license Several of these steps have their own fully documented procedures. We'll link you to those resources below. 1. Return the licenses you intend to upgrade The steps to return a standalone license are fully documented. Choose the link below that best matches your needs, depending on whether your PC can connect to the Internet: Standalone - Return - Online Standalone - Return - XML / Offline Be sure to return ALL licenses you wish to upgrade. 2. Upgrade your licenses NOTE: Licenses with expired maintenance will not upgrade. Timed licenses do not upgrade. Only permanent (not timed) licenses under current maintenance can be upgraded. Log in to your FlexSim Account. If you were already logged in to your FlexSim Account, in the top navigation menu hover over your initials icon and choose Reload Account. Now in the top navigation menu, choose Licenses > List. Check that the available seat count is equal to the total. All of a license’s seats should be returned for it to upgrade. Click on the Upgrade Licenses button. If you have several licenses to upgrade and all are owned by or shared with your FlexSim Account, they will all be upgraded at once. Please be patient while the upgrade process works in the background. When the page refreshes, eligible licenses will have a new activation ID for the latest version of the software. Your license code indicates its version at the end of the code to help you know what versions your license will properly activate. Review license code format. You'll be able to use the upgraded license codes in the next step. 3. Activate the upgraded licenses The steps to activate a standalone license are fully documented. Choose the link below that best matches your needs, depending on whether your PC can connect to the Internet: Standalone - Activation - Online Standalone - Activation - XML / Offline If you have any questions or problems, please search our Answers Community for possible solutions. There is a good chance someone else has already asked your question. Still not finding what you're looking for? Submit a new question and we'll check it out. If you're including any confidential information, such as license codes, be sure to mark your question as private! You can also contact your local FlexSim distributor for live phone, web, or email help.

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.

Neste Tutorial iremos demonstrar como funciona a ferramenta Model Layouts no FlexSim. Esta ferramenta permite que você crie e edite diferentes Layouts para um mesmo modelo. Você pode modificar a posição dos objetos e criar uma nova opção de Layout. Por exemplo você pode salvar um Layout inicial de seu processo e após montar propostas a serem estudadas, como um Layout com diferentes posições, redução de transporte, etc... O Model Layouts permite que você possa fazer isso. modellayouts-example-model.fsm Ferramenta útil para estudar comparativamente os resultados gráficos dos Layouts criados apenas rodando o modelo para cada um dos Layouts, e ou para criar a variável Layout para inclusão das opções de Layouts em um experimento. As informações de Layout são armazenadas em cada um dos objetos individuais. Um nó é adicionado aos atributos de objeto chamados Layouts. Para cada Layout criado, uma cópia das informações espaciais atuais do objeto (posição, tamanho, rotação) é armazenada. Janela Model Layout Esta janela pode ser acessada em: View Menu / Model Layouts Layout List - Exibe a lista de Layouts atuais. Selecione um layout para atualizar imediatamente o modelo desse Layout. Você pode renomear um Layout digitando um novo nome neste campo. Add Layout - Adiciona um novo Layout. Quando você adiciona um Layout, ele salva o Layout atual do modelo. Delete Layout - Remove o Layout selecionado. Set - Opção para atualizar o Layout do modelo selecionado para corresponder ao Layout atual do modelo indicado na lista (Layout List).

One of the most powerful commands in FlexSim is the query() command. It allows you to run SQL-like queries on virtually any data structure in the tree. If you don't know what that means, or what SQL is, or why it would be good to have SQL in FlexSim, this article is for you. If you have general ideas, but you would like to know more, then this article is for you. This article is not about connecting FlexSim to an external database. If that is your goal, then this article is not for you. Basics - Tables Data is often arranged in a table, which very loosely means that data is organized into rows and columns. However, SQL (and therefore the query() command) was designed to work only on certain kinds of tables, that look something like this: Name Age Fur Color Scooter 6 Brown Spot 3 Brown Whizby 4 Black Notice the following points about this table: Each column has a unique name There are no row headers (although if your table in FlexSim has data in the row header, that's okay; we'll get to that later) The table is a list of things, and each row in the table represents a single thing. The columns tell you the data that is stored about each thing. In this table, each thing is a pet, and each row stores the name, age, and hair color (the columns) of each pet. If our data included another pet, it would make another row in the table. In database lingo, a row in a table is called a record. One other thing you need to know about this table is that it has a name (in this case, "Pets"). All tables in SQL have a name, and follow the format described previously. Basics - Tables In FlexSim FlexSim has several different ways you can store data. Most users employ Global Tables and Lists (found in the toolbox) to manage data in their model. More advanced users sometimes create tables or bundles on labels. Then there's the model itself, which stores your object's locations in a tree data structure. All the data about where and object is, and how big it is, is stored in the model tree. So which of these data structures meet the standards for a SQL table? As far as the query() command is concerned, all of them do. The query() command is flexible enough to handle any data structure. The trick is to imagine your data as a table. To do this, you need to be able to answer the following questions: How many rows are there? What columns will the table have? How do you get the data for each cell? Phrased another way, given a row and a column, how do you put data in the table cell? If you can answer these questions, you can use the query() command. Let's apply these questions to two data structures in FlexSim: the Global Table, and the Global List. For the Global Table, the answers are very straightforward, but follow along to get the hang of it: Q: How many rows are there? A: The number of rows in the Global Table. Q: What columns with the table have? A: The same columns as in the Global Table. Q: How do you get the data for each cell? A: Given the row and column, look up the value in the Global Table For the Global List, things get a little more interesting: Q: How many rows are there? A: The number of entries on the list. Q: What columns with the table have? A: There is a value column, and there is a column for each field on the list. Q: How do you get the data for each cell? A: Remember that each row represents an entry on the list. For the value column, I get the value that was pushed on to the list to create the entry. For each field column, I get the value of the field for that entry. For example, suppose you have this list: Then supposed that you pushed a 5, 23, -12, 7, and 2 on to this list. When you view the entries on the list, you can see the data on this list laid out as a table: Notice that the value column has the values that were pushed on the list. The field columns (Doubled, Tripled, OddOrEven, and IsNegative) are each filled with the values of that field. The query() command has built-in support for Global Tables and Global Lists. However, it is always important to remember that to the query() command, the data is laid out in a table. If the data is not laid out in a table, you can still use the query() command, but you will need to use the methods explained in the Explicitly Defined Tables section. Basics - Queries SQL stands for Structured Query Language, so we can guess that it is a language for making queries. So what is a query? In a general sense, a query is a question. In SQL, a query is a question with two parts: who are you asking, and what do you want to know? There is a general answer to both parts of the question, and this is where tables come in. The answer to the first part (who are you asking?) is always a table. A SQL query is always directed at one (or more) tables. The answer to the second second part (what do you want to know?) is usually a new table. A SQL query takes in a table, and gives back a new table. The power in SQL comes from the new tables you can make. You can make a table that is a sorted version of the old table, like sorting data in excel. For example, if you have a list of items that need to be processed, you can sort that list by the item's priority. You can also make a table that is a filtered version of the old table, meaning you only kept certain rows. For example, if certain operators can only do certain tasks, you can make sure to only include the tasks that operator can do. In fact, you can make a table that is filtered, sorted, and modified in several other ways all with one query statement. Basics - Queries in FlexSim Let's look at examples of the query() command. You can follow along using the attached model ( numberlist.fsm). That model has a script that pushes values on to the list, and then queries the list. It also puts the result into the Global Table called QueryResult. Let's look at the line of that script with the query() command: int newTableRows = query("SELECT value FROM NumberList"); This line has a lot of new material. You can see that the query() command takes at least one argument, which is the text of a SQL query. We'll discuss the query itself in a moment. The query() command takes in the SQL query, and creates an internal (and invisible) temporary table that contains the result of the SQL query. It then returns the number of rows in the temporary table. Since you can't readily see the new table made by the query() command, you may want to copy the temporary table to a global table, using the dumpquery() command, as the script does: dumpquery(reftable("QueryResult"), 1); The temporary table lasts until you run the query() command again. Now for the query itself. You can see two parts of this query. The question "What do you want to know?" is answered by the SELECT statement. The question "Who are you asking?" is answered by the FROM clause. In this case, the FROM clause just lists one table, the NumberList. Recall that even though the NumberList isn't technically a table, you can visualize it's data as a table, which is what the query() command does (you can always right-click the NumberList in the Toolbox and choose the "View Entries" option to see the data as a table). In this example, the SELECT statement lists a column name. This means that the resulting table will have 1 column, because only one is required by the SELECT statement. When you run the script, it will put the result of the query in the QueryResult table: Notice that this table has only one column, the value column. If you look at the NumberList entries, you will see that this column is identical to the value column in that table. Examples To give you a general idea of what you can do with queries, these examples show a few common tasks. The examples all query the NumberList, which can be visualized as the following table: Selecting Multiple Columns SELECT value, IsNegative FROM NumberList Filtering SELECT value, IsNegative FROM NumberList WHERE IsNegative == 1 SELECT value, OddOrEven FROM NumberList WHERE value >= 5 Sorting SELECT value, Doubled FROM NumberList WHERE value >= 5 ORDER BY value Advanced - Callback Values It is often necessary to create a dynamic query. In FlexSim (not in regular SQL), you can do this by replacing a value in a query with a $n variable. This variable corresponds to additional parameters in the query() command. If you specify $1, then the value in the query will be the first additional parameter in the query() command, $2 will correspond to the second, and so on, up to $9. For example: query("SELECT Col1, Col2 FROM MyTable WHERE Col1 > $1 AND Col2 < $2", 10, 20) This query creates a table with Col1 and Col2, but only the rows where Col1 is greater than 10, and Col2 is less than 20. It is possible to include the values 10 and 20 in the query text. However, the $ variables allows you to easily change the value in the query, and replace them with more complicated expressions. Note that using callback values in a query where the FROM value is a Global List is not supported before versions 16.0.6/16.2.1. Advanced - Explicitly Defined Tables and the $iter() command Another FlexSim-specific feature of the query() command is the ability to explicitly define a table. This means you can query data that isn't arranged in the table format. In order to do so, you will need to answer the questions posed above, but shown again here: How many rows are there? What columns will the table have? How do you get the data for each cell? Once these questions are answered, the query() command can treat your data like a table. Each of the following subsections will answer these questions in detail. Defining the Number of Rows Let's start with a simple example: query("SELECT 1 FROM $1", 5) Notice that we are selecting from a number, not a Global Table or Global List. When the query() command sees a number instead of a table in the from statement, it assumes that you are querying a table with that number of rows. The statement above yields the following table (after a call to the dumpquery() command): This table has five rows, because $1 (the first additional parameter) evaluates to 5. All the rows have the value 1 because SELECT can handle expressions as well as column names (or expressions involving column names). Note that defining a table will only work if you use callback variables. A from statement like FROM 5 is not valid. To determine the number of rows in the table, use callback variables in the FROM statement. Defining the Columns To define the columns of your table, use the SELECT statement. Each expression in the SELECT statement will result in a column. When you are explicitly defining a table, you will often use callback variables as columns. This is where we can take advantage of the query() command. The query() command is very different from most other commands, because most commands only evaluate their parameters once. The query() command, however, can evaluate its parameters as many times as it needs to. Let's look at another example: query("SELECT $2 FROM $1", 5, normal(0, 1)) The result of this query is the following table: Notice that the second parameter, corresponding to $2, was re-evaluated as many times as the query needed it. Getting the Value in Each Cell Finally, we need a way to access the correct value for a given row and column. To do that, we need a way to know which row we are currently dealing with. This is where the $iter() command comes in. For example: query("SELECT $2 FROM $1", 5, $iter(1)) The $iter() command accepts an argument. That argument should match the value of the callback variable, e.g. if you used FROM $1, then the $iter() command should take a one as an argument. The $iter() command is linked to the query() command, so that its return value depends on which row is being evaluated. The above query results in the following table: Notice that $iter(1) returned the row number for each row. Now we can begin to query the tree, as if it were a table. Let's start with a simple example. Suppose you wanted a table of all the names of the first-level subnodes of the model tree. Let's start by answering the three questions: Q: How many rows are there? A: The number of first-level subnodes of the model Q: What columns with the table have? A: A column for the name of each of those subnodes Q: How do you get the data for each cell? A: Given the row number, get the name of that object Let's translate those answers into a query. First, we need to query something that isn't in table format already, so we know we need to use callback variables in the FROM statement: query("SELECT ... FROM $1", ..., ...) Next, we need a column for the names of all the subnodes, so we add one to the select statement: query("SELECT $2 FROM $1", ..., ...) Next, we need to answer the question of how many rows there are. Since this is the number of subnodes, you can write that as content(model()): query("SELECT $2 FROM $1", content(model()), ...) Finally, we need a way to get the name of each of the subnodes. We know that $iter(1) will give us the values from 1 to content(model()), so we can use those values in the rank() command, and we can pass the result of the rank() command to the getname() command: query("SELECT $2 FROM $1", content(model()), getname(rank(model(), $iter(1))) ) After dragging in a few random objects into the model, you can run that query. If you use the dumpquery() command, you can get a table like this: In the previous example, we used the value from $iter(1), and passed it in to rank(), and from rank() to getname(), all to get the name of the nth subnode of the model. Since querying a node in this way is fairly common, the query() command also allows you to specify a node as a table, rather than a number. In this case, $iter(1) will iterate over all the subnodes of $1, rather than the values 1 to $1. This makes our query much simpler: query("SELECT $2 FROM $1", model(), getname($iter(1))) Advanced - Flattening Data There is another option for what you can query in a FROM statement. If you use a callback variable (like $1) as your table, then you can use flattening syntax, shown in the following example: query("SELECT $3, $4 FROM $1x$2", 3, 2, $iter(1), $iter(2)) This query makes the following table: Notice that for every possible value of $1, there is a row for every possible value of $2. That is the purpose of the x (called the flattening operator); it ensures that there is a row for each permutation of all the callback variables involved. A query containing FROM $1x$2x$3x$4 would produce a table with enough rows for each unique combination of $iter(1), $iter(2), $iter(3), and $iter(4), and then execute the query on that table. The user manual contains an excellent example of when flattening syntax might be helpful, shown in the help manual in Miscellaneous Concepts > SQL Queries > Example.

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.

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.

Neste Tutorial iremos demonstrar em um exemplo como funciona a biblioteca AStar Navigator no FlexSim. O AStar Navigator, também conhecido como A*, é um algoritmo de busca usado para encontrar um caminho entre pontos, e serve para determinarmos o trajeto pelo qual os executores de tarefas podem se movimentar pelo modelo. Esta biblioteca permite que você crie e defina barreiras físicas para a correta movimentação dos executores de tarefas em seu modelo. Nós iremos usar o seguinte modelo para mostrar como o A* Navigator pode ser usado em um modelo simples. astar-example-model.fsm Crie o A* Navigator Primeiro, um objeto AStarNavigator deve ser adicionado ao modelo. Somente um objeto AStarNavigator faz-se necessário e permitido por modelo. Crie um objeto AStarNavigator ao clicar e arrastar da biblioteca para qualquer posição na superfície de simulação em 3D. Conectando os Membros Neste modelo, existe apenas um objeto executador de tarefa (TaskExecuter), no entanto, nós também queremos incluir o Rack como uma barreira. Faça um conexão com o 'A' entre o AStarNavigator e o operador. Isto pode ser feito mantendo a tecla A pressionada e clicando/arrastando do AStarNavigator para o operador, ou do operador para o AStarNavigator (não importando a ordem ou sequência de onde tem que partir a conexão). Um círculo em azul irá aparecer abaixo do operador. Faça uma conexão com o 'A' entre o AStarNavigator e o Rack. Um retângulo em azul irá aparecer abaixo do Rack. Adicione um Source e um Queue próximo ao operador conforme você pode visualizar em outra imagem mais abaixo. Criando Barreiras (Barriers) Junto com o Rack, vamos também criar um par de barreiras para representar paredes ou obstáculos que o operador não pode caminhar através. Clique no ícone do Divider na biblioteca para entrar no modo de criação. Clique em algum lugar ao lado direito do Queue (buffer) para criar um novo Divider. Clique duas vezes mais próximo dos pontos para mostrar a imagem abaixo para finalizar o Divider. Clique com o botão direito do mouse para sair do modo de criação. Adicione os Processors e um Sink conforme imagens abaixo. Faça a conexão deste o Source até o Sink usando a conexão com “A”. Clique sobre o ícone Barrier na biblioteca para entrar no modo de criação. Clique uma vez onde o canto esquerdo inferior do Barrier estará como mostrado abaixo. Clique novamente no canto direito superior para completar a configuração do Barrier. Clique com o botão direito para sair do modo de criação. Coloque o Barrier abaixo do Rack. Execute o Modelo Você pode agora resetar e executar o modelo para ver como será a performance do operador. Lembre-se, se você fizer qualquer mudança nas suas barreiras, o modelo obrigatoriamente deve ser resetado antes de ser executado novamente. Note que o operador encontrou o menor caminho para movimentar-se por cima e por fora do Divider. Embora exista diversas formas de alterar os caminhos do operador (por exemplo, estender ainda mais o tamanho do Divider), nós iremos modificar o caminho percorrido pelo operador, usando o Preferred Path. Crie Preferred Paths Preferred paths não são caminhos “configuráveis”, em vez disso, dará aos nodes associados com o caminho preferido, um peso maior no algoritmo de busca. Isso vai nos afetar, e puxar o operador para o caminho preferido. Clique sobre o ícone Preferred Path na biblioteca para entrar no modo de criação. Crie os dois seguintes Preferred Paths conforme mostrado na imagem abaixo. Preferred paths são unidirecionais e além do mais precisa ser posicionado no layout na ordem correta. Clique com o botão direito do mouse para sair do modo de criação. Execute o Modelo Resete e execute o modelo. Se o seu operador continuar a movimentar para cima e fora do Divider, você pode ou movimentar o Preferred Path ou alterar o Preferred Path weight na janela de propriedades do objeto AStarNavigator. Os Resultados do seu modelo podem variar deste exemplo conforme você posiciona suas barreiras e objetos, o que pode fazer a diferença no cálculo dos caminhos do operador. AStar Navigator Library O AStar é acessado na Biblioteca principal a esquerda: View Menu / Drag-Drop Library Existem 5 tipos de barreiras usada pelo A* Navigator. Estas barreiras modificam a grade usada no algoritmo de busca. Nota: Uma vez que as barreiras são criadas ou modificadas, o modelo precisa ser Resetado para recalcular o node table. Solid Barrier A mais simples das barreiras, a barreira sólida modifica a grade para remover uma área retangular, prevenindo os membros de viajar e (travel members) se movimentarem dentro da barreira. Divider Dividers desconectam os nodes ao longo de seu caminho, prevenindo os travel members de atravessarem o divider. Dividers podem ser modificados na superfície de simulação 3D ao arrastar o ponto final e intermediário. Qualquer número de pontos pode ser adicionado ao divider. One-Way Divider O One-way divider funciona de forma muito similar ao divider, no entanto, travel members são permitidos se movimentarem através do divider na direção das flechas em verde, neste caso, em direção ao topo da página. O one-way dividers pode ser modificado na superfície de simulação em 3D ao arrastar os pontos finais ou intermediários. Qualquer número de pontos podem ser adicionados em um one-way divider. Preferred Path Embora o preferred path não é uma barreira real, ele funciona da mesma forma que as barreiras fazem para modificar a tabela de nodes do A* Navigator. Em vez de modificar os nodes removendo os seus indicadores de direção, o caminho preferencial dá um peso maior a todos os nós associados com o percurso. Este valor de Path Weight pode ser alterado através da janela de propriedades do A * Navigator. O Path Weight tem de ser maior do que 0 e menor que 1, a fim de funcionar adequadamente. Valores acima ou abaixo deste podem causar resultados não intencionais. Os preferred paths podem ser modificados na visualização em 3D, arrastando os pontos do fim ou do meio. Preferred paths são unidirecionais. Qualquer número de pontos pode ser adicionado a um preferred path.

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.

Neste exemplo passo a passo iremos demonstrar como fazer uma otimização em seu modelo no FlexSim, utilizando o Optimizer, ferramenta OptQuest da OptTek, a qual é um add-in opcional no FlexSim. Com esta ferramenta você incorpora Metaheurísticas e orienta seu algoritmo para Otimizar, buscar as melhores soluções. Essa abordagem utiliza soluções funcionaram bem e as recombina em novas e melhores soluções. Vamos lá! Assista o vídeo em nosso canal do YouTube e acompanhe a montagem do modelo passo a passo abaixo: Modelo de Otimização Passo a Passo Para este tutorial, vamos examinar uma situação muito simples. Um único operador carrega o item de uma fonte para um processador. Depois que o item é processado o operador o carrega para um segundo processador que leva mais tempo para processar do que o primeiro. Após o segundo processador termina de processar o item, o operador leva-o para a saída. Agora vamos supor que queremos aumentar a Produção (que também está vinculado à receita) deste sistema, ajustando a posição dos processadores. Se cada processador pudesse ser movido até três metros à direita ou à esquerda, onde cada um deveria ser colocado? Seria muito difícil intuitivamente saber como colocar ambos os processadores para maximizar a produção. A fim de resolver este problema com precisão, vamos usar o Otimizador. Agora, obviamente este é um cenário drasticamente simplificado, mas muitas vezes na vida real você tem situações em que você quer ver como vários layouts afetam a Produção geral. Esta é uma implementação muito simplista de tal experiência. Passo 1: Construindo o Modelo Modelo Crie um novo modelo usando Segundos, Metros e Litros para unidades. Objetos Crie um Source, dois Processors, um Sink, um Dispatcher, e um Operator. Coloque esses objetos como mostrado abaixo e faça as conecções. Posições Defina a localização dos objetos de acordo com a tabela abaixo: Dispatcher e Operator não precisam estar em um lugar específico, mas não devem estar alinhados com o resto dos objetos. Lógica Defina a seguinte lógica: Selecione no Source1, Processor2, e Processor3 para usar transporte (Use Transport disponível no menu de propriedades rápidas (Quick Properties). Selecione o tempo de processo para o Processor2: normal(10, 2) (também disponível no disponível no menu Quick Properties). Selecione o tempo de processo para o Processor3: normal(12, 3). Defina a posicão inicial do Operator na sua posição atual. Passo 2: Definindo o Experimento O restante deste tutorial trata do uso do Experimenter, encontrado no menu Statistics. O Otimizador usa a maioria das funcionalidades já presentes no experimentador. Criando Variáveis Abra a janela Experimenter. Posicione a janela para que você possa ver os processadores no modelo, bem como a janela. Em seguida, para Processor1 e, em seguida, Processor2, siga estas etapas: Clique no processador na vista 3D. Clique no botão Referência de Posição nas Propriedades Rápidas e defina a referência de posição para Direct Spatials. Clique na seta para baixo ao lado do botão +. Selecione Sample no menu variables. Isso coloca o cursor no modo de Amostra. Selecione uma amostra do campo de posição X no menu Propriedades Rápidas clicando nele. Isso adiciona uma nova variável no Experimenter. Defina o valor para o Cenário 1 da nova variável clicando duas vezes na célula e digitando o novo valor. Defina o nome da variável clicando duas vezes no nome atual. Defina o nome sendo Proc1X para o Processor1 e Proc2X para o Processor2. Criando Performances de Medida Selecione a aba Performance Measures na janela do Experimenter, então: Clique no botão + para adicionar uma nova medida de desempenho. Nomeie a nova medida de desempenho Produção. Clique no botão e selecione a primeira opção Statistic by individual object. Selecione o Sink para o objeto e Input para a estatística. Para selecionar o objeto simplesmente digite "/Sink" (sem aspas) no campo do objeto ou faça o seguinte: Clique no botão +. Selecione o Sink através da lista de objetos do modelo. Após clique no botão Select quando você terminar. Otimização Além de utilizar o Experimenter para definir explicitamente cenários, você pode usar o Otimizador. O Optimizer criará automaticamente cenários e, em seguida, testará esses cenários, tentando encontrar um cenário que melhor atenda a um objetivo. Projetando a Otimização Vá para a guia Design do Optimizador na janela do Experimenter. Você verá que as duas variáveis criadas anteriormente estarão presentes; Isso ocorre porque o experimentador e o otimizador compartilham as mesmas variáveis. No entanto, o otimizador precisa de informações adicionais sobre essas variáveis. Especificamente, você deve especificar: Type - O tipo de uma variável determina quais tipos de valores são possíveis para uma determinada variável. Variáveis contínuas podem ter qualquer valor entre o limite superior e inferior. Lower Bound - O limite inferior especifica o menor valor possível que o otimizador pode definir para a variável. Upper Bound - O limite superior especifica o valor mais alto possível que o otimizador pode definir para a variável. Step - Para Variáveis Discretas e Design, o passo especifica a distância entre valores possíveis, começando pelo limite inferior. Group - Para as variáveis de permutação, o grupo especifica qual conjunto de variáveis de permutação essa variável particular pertence. Para esta otimização, queremos permitir que os processadores se movam três metros para cada lado. Como não estamos limitados a posições específicas dentro desse intervalo, ambas as variáveis de posição são Contínuas. No entanto, precisamos definir os limites inferior e superior de cada variável. Para editar valores na tabela, clique duas vezes na célula de interesse e insira o novo valor. Insira os valores mostrados abaixo: O passo final do projeto é definir a função objetivo. A função objetivo está presente, mas em branco. Edite seu nome para Faturamento. Em seguida, clique no campo da função de seta. Um botão aparecerá no lado direito. Clique neste botão para exibir uma lista de todas as variáveis e medidas de desempenho. A função objetivo é um valor derivado de qualquer um ou de todos esses valores. Selecionar Produção, Isso irá adicionar essa medida de desempenho para a função objetivo, e colocar o cursor para a direita e para o final. Adicione o texto * 500 para que a receita seja igual o [Produção] * 500. Deixe a direção em Maximize, porque queremos maximizar o Faturamento. Como temos apenas um objetivo, o modo de pesquisa pode permanecer em Single. Passo 3: Executando a Otimização Vá para a aba Optimizer Run na janela do Experimenter. Então: Defina Run Time sendo 10000. Este é o tempo que o otimizador executará cada configuração do modelo (potenciais soluções) para a avaliação. Defina o Wall Time sendo 0. Normalmente, isso significa quanto tempo o otimizador pode ser executado em tempo real. O valor 0 significa que não tem limite de tempo. Defina Max Solutions como 50. Isso significa que o otimizador tentará não mais de 50 soluções diferentes para encontrar a solução ideal. Clique no botão Optimize. A janela do Experimenter alternará automaticamente para a guia Resultados do Otimizador, Optimizer Results. O otimizador então começará a executar a seguinte sequência: Determinar valores para Proc1X e Proc2X. Executar um modelo com esses valores para 10000 segundos. Avaliar as variáveis e medidas de desempenho. Calcula a função objetivo. Classifique esta solução. Usa as informações desta solução para criar uma nova solução - novos valores para Proc1X e Proc2X. Repete novamente a partir do passo 2. O otimizador pode avaliar várias soluções ao mesmo tempo. À medida que a otimização progride, o gráfico de Resultados do Otimizador é atualizado e mostra o progresso do otimizador. Uma vez que o otimizador avalie 50 soluções, uma mensagem aparecerá indicando por que o otimizador parou. Neste caso, ele dirá que o otimizador atingiu o número máximo de soluções. Se algo der errado, a mensagem conterá informações sobre o erro. Passo 4: Analizando os Resultados Assim que a otimização for concluída, o gráfico de resultados do otimizador será semelhante a este: O Eixo Y é chamado de "Single Objective". Para este exemplo, é sinônimo de Faturamento. As melhores soluções são destacadas. Os círculos com uma borda mais clara ao seu redor representam melhores soluções. Para um único objetivo, as 10 melhores soluções são marcadas desta forma. Como a otimização progrediu, o otimizador ficou melhor e melhor na criação de boas soluções, de modo que as últimas 15 soluções foram todas muito boas. Isso é chamado de convergência, e é uma maneira de saber se uma otimização é concluída; Se o valor objetivo não tiver melhorado por um tempo, pode ser que ele não melhore com mais pesquisas, e a melhor solução atual deve ser usada. Respondendo à Pergunta Inicial O objetivo dessa otimização foi descobrir onde posicionar os dois processadores. Agora podemos encontrar a resposta a esta pergunta com muita facilidade. Passe o mouse sobre a melhor solução (o maior círculo azul) no gráfico; Uma pequena janela aparecerá. Clique nesta solução para selecioná-la. Agora, no painel Opções de gráfico, altere o Eixo Y para Proc1X e o Eixo X para Proc2X. A melhor solução (e todas as outras melhores soluções) é encontrada onde Proc1X é maior, e onde Proc2X é menor. Lembre-se que todas as 10 melhores soluções produziram os mesmos resultados; Neste caso, ter os dois processadores próximos um do outro é a melhor configuração para este modelo. Configurando o Modelo para a Melhor Solução Pode ser muito útil configurar o modelo para visualizar a melhor solução. Para fazer isso, clique no botão Export Scenarios. Este botão leva todas as soluções selecionadas e cria cenários para elas. Volte para a guia Scenarios na janela Experimenter para ver a nova solução. Agora, a partir do menu suspenso " Choose default reset scenario" na extrema direita, selecione o novo cenário. Em seguida, resete o modelo para aplicar esses valores ao modelo 3D. Segue o modelo referente ao artigo: modelo-optimizer.fsm Inscreva-se e acompanhe nosso canal de videos no YouTube FlexSim Brasil