In light of rising cases on campus and a lack of mask wearing indoors in public, OSU administration and I met yesterday afternoon to discuss additional COVID protocols for our campus. While more communications will be coming out this week, we wanted to provide an immediate update about masks on campus. With evidence that the Delta variant is more than twice as infectious and is leading to increased transmissibility when compared to other variants, even in vaccinated individuals, we must be vigilant as a campus community.
With that in mind, we expect masks to be worn indoors, in public on campus. This includes classrooms, laboratories and all indoor meetings and gatherings. Masks are being made widely available across the campus so that all students and employees will have access to masks. We have updated our campus signage to reflect this expectation so that you may come to campus prepared and immediately download, print and post these signs in your respective areas. The town hall will be streamed live on OState.
Town Hall Meeting - Thursday 4pm. Need Assistance? All Simio license types provide limited logging capabilities; Academic RPS licenses provide additional related capabilities. Additional feature descriptions and details are available in the Simio Help and SimBits. For this example, we will use Model and will log the ATM resource usage and create a related dashboard report. First we will tell Simio to log the resource usages for the ATM server resource.
The steps to do this are as follows:. Turn on resource usage logging for the ATM server object. Navigate to the Logs section of the Results tab and select the Resource Usage Log if it is not already selected. Now that the individual resource usages are logged, we will create a simple dashboard report that plots the usage durations over the simulation time.
The steps are as follows:. Drag the Duration Hours item and drop it on the Values Pane 1 data item. Click on the bar chart item just to the right of the data item and change the chart type to a line plot. Open the drop-box for the data source and select the Date-Hour-Minute option from the list. The chart plots the resource usage durations by the start time of the usages. Animation generally takes place in the Facility Window.
If you click in the Facility Window and hit the H key, it will toggle on and off some tips about using the keyboard and mouse to move around the animation. You might want to leave this enabled as a reminder until you get familiar with the interface.
The models in Figures 4. To switch between 2D and 3D view modes, just tap the 2 and 3 keys on the keyboard, or select the View ribbon and click on the 2D or 3D options. In 3D mode, the mouse buttons can be used to pan, zoom, and rotate the 3D view.
The model shown in Figure 4. If you click on any symbol or object, the Symbols ribbon will come to the front. This ribbon provides options to change the color or texture applied to the symbol, add additional symbols, and several ways to select a symbol to replace the default.
In the Symbols ribbon now displayed, if you click the Apply Symbols button, you will see the top section of the built-in library as illustrated in Figure 4. The entire library consists of over symbols organized into 27 categories. To make it easier to find a particular symbol, three filters are supplied at the bottom: Domain, Type, and Action.
You can use any combination of these filters to narrow the choices to what you are looking for. Near the top you will see a Library People category.
The entity in your model should now look similar to that in Figure 4. Note that under the People folder there is an folder named Animated that contains symbols of people with built-in animation like Walking, Running, and Talking.
Using these provides even more realistic animation, but that is probably overkill for our little ATM model. You may notice that Figure 4.
Unfortunately this was not one of the symbols in the library. If you happened to have an ATM symbol readily available you could import it. But for the rest of us Simio provides a much easier solution — download it from Trimble 3D Warehouse.
This is a huge repository of symbols that are available free, and Simio provides a direct link to it. Note that the library is updated frequently, so your specific search results may vary.
You can click on an interesting object we chose a Mesin ATM and see the basic details such as file size. If you click on the See more details link, you can view and rotate the model in 3D from the browser. If you are satisfied, choose Download and save the skp file on your computer you may have to set up an account on the 3D warehouse site if you do not already have one in order to download symbols.
Back in Simio, you can import the symbol and apply it to the selected Server using the Import Symbol icon with the Server object instance selected. This will import the 3D model into your Simio model, allow you to change the name size and orientation of the symbol, and apply it to the object instance. Once the symbol has been imported, it can be applied to other object instances without re-importing using the Apply Symbol icon.
One of the most important things to verify during the import process is that the size in meters is correct. You cannot change the ratio of the dimensions, but you can change any one value if it was sized wrong.
In our case our ATM is about 0. Now your new Model should look something like to Figure 4. If you change to the 3D view 3 key you should see that those new symbols you selected also look good in 3D, as in Figure 4.
You could draw walls see the Drawing ribbon , or add features like doorways and plants. You can even import a schematic or other background to make your model look even more realistic. As hard as it may be to believe, sometimes people make mistakes. When those mistakes occur in software they are often referred to as bugs.
Many things can cause a bug including a typo typing a 2 when you meant to type a 3 , a misunderstanding of how the system works, a misunderstanding of how the simulation software works, or a problem in the software.
Even the most experienced simulationist will encounter bugs. In fact a significant part of most modeling efforts is often spent resolving bugs — it is a natural outcome of using complex software to model complex systems accurately. It is fairly certain that you will have at least a few bugs in the first real model that you do.
How effectively you recognize and dispatch bugs can determine your effectiveness as a modeler. In this section we will give you some additional insight to improve your debugging abilities. The best way to minimize the impact of bugs is to follow proper iterative development techniques see Section 1. If you work for several hours without stopping to verify that your model is running correctly, you should expect a complex and hard-to-find bug.
Instead, pause frequently to verify your model. When you find problems you will have a much better idea of what caused the problem and you will be able to find and fix it much more quickly. The most common initial reaction to a bug is to assume it is a software bug. Although it is certainly true that most complex software, regardless of how well-written and well-tested it is, has bugs, it is also true that the vast majority of problems are user errors.
Own the problem. Assume that it is your error until proven otherwise and you can immediately start down the path to fixing it. How do you even know that you have a problem?
Many problems are obvious — you press Run and either nothing happens or something dramatic happens. But the worst problems are the subtle ones — you have to work at it to discover if there even is a problem.
Comparing the model results to our expectations is the first and best way to discover problems. The following steps extend that verification a bit deeper. Enhance the animation to be more informative.
Use floating labels and floor labels to add diagnostic information to entities and other objects. Examine the output statistics carefully. Are the results and the relationships between results reasonable?
For example is it reasonable that you have a very large queue in front of a resource with low utilization? Add custom statistics to provide more information when needed.
Finally, the same debugging tools described below to help resolve a problem can be used to determine if any problem even exists. Okay, you are convinced that you have a bug. And you have taken ownership by assuming for now that the bug is due to some error that you have introduced.
Good start. Now what? There are many different actions that you can try, depending on the problem. Look through all of your objects, especially the ones that you have added or changed most recently. Look at all properties that have been changed from their defaults in Simio these are all bold and their categories are all expanded.
Ensure that you actually meant to change each of these and that you made the correct change. Look at all properties that have not been changed from their defaults. Ensure that the default value is meaningful; often they are not. Minimize entity flow. Limit your model to just a single entity and see if you can reproduce the problem. If not, add a second entity. It is amazing how many problems can be reproduced and isolated with just one or two entities.
A minimal number of entities help all of the other debugging processes and tools work better. In Simio, this is most easily done by setting Maximum Arrivals on each source to 0 , 1 , or 2. Minimize the model. Save a copy of your model, then start deleting model components that you think should have no impact. If you delete too much, simply undo, then delete something else. The smaller your model is, the easier it will be to find and solve the problem.
If you encountered a warning or error, go back and look at it again carefully. Sometimes messages are somewhat obscure, but there is often valuable information embedded in there. Try to decode it. Follow your entity ies step by step. Understand exactly why they are doing what they are doing. If they are not going the way they should, did you accidentally misdirect them? Or perhaps not direct them at all? Examine the output results for more clues.
Change your perspective. Try to look at the problem from a totally different direction. If you are looking at properties, start from the bottom instead of the top. If you are looking at objects, start with the one you would normally look at last. This breaks the pattern-recognition cycle that sometimes allows people to see what they expect or want to see rather than what is really there. Enlist a friend. If you have the luxury of an associate who is knowledgeable in modeling in your domain, he or she might be of great help solving your problem.
But you can also get help from someone with no simulation or domain expertise — just explain aloud the process in detail to them. In fact, you can use this technique even if you are alone — explain it to your goldfish or your pet rock. While it may sound silly, it actually works. Explaining your problem out loud forces you to think about it from a different perspective and quite often lets you find and solve your own problem! Okay, no one likes to read manuals.
But sometimes if all else fails, it might be time to crack the textbook, reference guide, or interactive help and look up how something is really supposed to work.
In fact you might get better results if you start at the bottom or skip around. But definitely use the debugging tools discussed below to facilitate this debugging process. Although animation and numerical output provide a start for debugging, better simulation products provide a set of tools to help modelers understand what is happening in their models.
Trace provides a detailed description of what is happening as the model executes. It generally describes entity flow as well as the events and their side-effects that take place. Until you learn about processes, Simio trace may seem hard to read, but once you understand Steps, you will begin to appreciate the rich detail made available to you. The Simio Trace can be filtered for easier use as well as exported to an external file for post-run analysis. Break provides a way to pause the simulation at a predetermined point.
The most basic capability is to pause at a specified time. Much more useful is the ability to pause when an entity reaches a specified point like arrival to a server. More sophisticated break behavior is available in Simio via the Break Window.
Watch provides a way to explore the system state in a model. Typically when a simulation is paused you can look at model and object-level states to get an improved understanding of how and why model decisions and actions are being taken and their side effects. In Simio, watch capability is found by right-clicking on any object.
Step allows you to control model execution by moving time forward by a small amount of activity called a step. This allows you to examine the actions more carefully and the side effects of each action.
Simio provides two step modes. When you are viewing the facility view, the Step button moves the active entity forward to its next time advance. When you are viewing the process window the Step button moves the entity token forward one process step. Profiler is useful when your problem is related to execution speed. It provides an internal analysis of what is consuming your execution speed.
Identification of a particular step as processor intensive might indicate a model problem or an opportunity to improve execution speed by using a different modeling approach.
Search provides an interactive way to find every place in your project where a word or character string like a symbol name is used. Trace, Break, Watch, and Step can all be used simultaneously for a very powerful debugging tool set. Combining these tools with the debugging process described above provides a good mechanism for better understanding your model and producing the best results.
In most cases these windows open automatically as a result of some action. For example when you enable trace on the Run ribbon, the Trace window will open. If you cause a syntax error while typing an expression, the Errors window will open.
But sometimes you may want to use these buttons to reopen a window you have closed e. The black circle indicates the button used to display the Trace window and turn on the generation of model trace. You can see the trace from the running model until execution was automatically paused a break when the Break point set on the Server2 entry node red circle is reached. At that point the Step button blue circle was pushed and that resulted in an additional 11 lines of trace being generated as the entity moves forward until its next time advance yellow background.
The Watch window on the right side illustrates using a watch on Server2 to explore its input buffer and each entity in that buffer.
In the default arrangement, these debugging windows display as multiple tabs on the same window. You can drag and drop the individual windows to reproduce the window arrangement in Figure 4. Since these windows can be repositioned even on other screens, sometimes you might lose track of a window. In this case press the Reset button found on the Project Home ribbon and it will reset those window positions back to their default layout.
Along the way, we integrated statistical analysis of simulation output, which is just as important as modeling in actual simulation projects, via topics like replications, run length, warm-up, model verification, and the analysis capabilities made possible by the powerful SMORE plots. We started out with an abstract queueing model, and added some interesting context in order to model a somewhat realistic queueing system.
In the process, we also discussed use of Simio Paths to model entity movement and basics of animation with Simio. All of these Simio and simulation-related topics will be covered in more detail in the subsequent chapters, with more interesting models. Run your model for hours and report the number of entities that were created, the number that completed service, and the average time entities spend in the system. Develop a queueing model for the Simio model from Problem 1 and compute the exact values for the steady state time entities spend in the system and the expected number of entities processed in hours.
Using the model from Problem 1, create an experiment that includes replications. Experiment with the various SMORE plot settings — viewing the histogram, rotating the plot, changing the upper and lower percentile values. If you run the experiment from Problem 3 five or any number of times, you will always get the exact same results even though the interarrival and service times are supposed to be random.
Why is this? You develop a model of a system. As part of your verification, you also develop some expectation about the results that you should get. When you run the model, however, the results do not match your expectations. What are the three possible explanations for this mismatch? In the context of simulation modeling, what is a replication and how, in general, do you determine how many replications to run for a given model?
What is the difference between a steady-state simulation and a terminating simulation? What are the initial transient period and the warm-up period for a steady-state simulation? Replicate the model from Problem 1 using Simio processes i. Compare the run times for this model and the model from Problem 1 for 50 replications of length hours. Run the ATM model Model for 10 replications of length hours 10 days.
What are the maximum number of customers in the system and the maximum average number of customers in the system recall that we mentioned that our model would not consider the physical space in the ATM. Was our assumption reasonable that we did not need to consider the physical space, that is?
Animate your model from Problem 1 assuming that you are modeling a cashier at a fast food restaurant — the entities represent customers and the server represents the cashier at the cash register. Modify your model from Problem 1 assuming that you are modeling a manufacturing process that involves drilling holes in a steel plate. The arrival rate should be parts per hour and the processing rate should be 50 parts per hour.
Use Trimble 3D Warehouse to find appropriate symbols for the entities steel plates and the server a drill press or other hole-making device. Add a label to your animation to show how many parts are being processed as the model runs. Build Simio models to confirm and cross-check the steady-state queueing-theoretic results for the four specific queueing models whose exact steady-state output performance metrics are given in Section 2. Remember that your Simio models are initialized empty and idle, and that they produce results that are subject to statistical variation, so design and run Simio Experiments to deal with both of these issues; make your own decisions about things like run length, number of replications, and Warm-up Period, possibly after some trial and error.
All time units are in minutes, and use minutes as well throughout your Simio models. You may need to do some investigation about properties of the gamma distribution, perhaps via some of the web links in Section 6. Remember that your Simio model is initialized empty and idle, and that it produces results that are subject to statistical variation, so design and run a Simio Experiment to deal with both of these issues; make your own decisions about things like run length, number of replications, and Warm-up Period, possibly after some trial and error.
All time units are in minutes, and use minutes as well throughout your Simio model. Test your automotive troubleshooting skills in this online engine management simulator and get a high score. To schedule a test give us a call or email: Phone: Whether you use computer software or a paper ledger to track expenses, you can set You will write a C program to implement a simulator with different scheduling algorithms.
This C program will simulate SJF scheduling. Schedule a Task. A round-robin scheduler Scheduling simulator c Press team. CPUSS was designed to be a framework that allows you to quickly and easily design and gather metrics for custom CPU scheduling strategies.
A larger time step size may be appropriate for circuits that run in real time. The head is initially at cylinder number 63 moving towards larger cylinder numbers on its servicing pass. Jetpack JW1 "SkyTraveler" 0. It is the ideal tool for workshops wanting to test their code. I'm developing a unix like shell which will provide all the file handling commands similar to unix.
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Simulation results confirm that the proposed incremental cost function can be incorporated into matching and scheduling algorithms to produce schedules where the effect of failures of machines and network resources on the execution of the application is reduced and the execution time of theApplication is minimized as well.
You will write a C program to implement a simulator with different scheduling algorithms. Using this You will write a C program to implement a simulator with different scheduling algorithms. For some businesses, it may be as simple as scheduling all your employees to work 8 a. Smaller time steps make the simulation more accurate, but slower. Simple said: when getting a mortgage the qualifying income is determined by the money you pay taxes on.
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Objectives: This project is to simulate a few CPU scheduling algorithms discussed in the class. Given n processes with their burst times, the task is to find average waiting time and average turn around time using FCFS scheduling algorithm. This tool has been developed for students to understand the concepts of the Tomasulo's algorithm used for Dynamic Scheduling.
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Schedule C is filed by: Sole proprietorships; Single-person LLCs who did not make an election to You will write a C program to implement a simulator with different scheduling algorithms.
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