For this tutorial, let us examine a very simple situation. A single worker must carry an item from a source to a processor. After the item finishes processing, the worker must carry it to a second processor that takes longer than the first. After the the second processor finishes the item, the worker then carries it to the sink.
Now we want to see if we can maximize the throughput of this system by adjusting (which is also tied to revenue) the position of the processors. If each processor could be moved up to three meters right or left, where should each be placed? It would be very difficult to intuitively know how to place both processors to maximize throughput. In order to solve this problem accurately, we will use the Experimenter and Optimizer.
Obviously this is a drastically simplified scenario, but often in real life you have situations where you want to see how various layouts affect overall throughput. This is a very simplistic implementation of such an experiment.
In this step, you'll build a basic 3D model for this tutorial. When you're finished, your model should look similar to the following image:
To build this model:
|Object||X Position||Y Position|
Check to ensure your model looks similar to the image shown at the beginning of this step.
Open the Experimenter window by selecting it from the Statistics menu of the Toolbox. Position the window so you can see the processors in the model as well as the window. Then, for Processor2 and then Processor3, follow these steps:
Sample the X position field in the Quick Properties menu by clicking on it. This adds a new experiment variable.
Set the value of Scenario 1 for the new variable by double-clicking the cell and entering the new value.
Set the name of the variable by double-clicking on the current name. Set the
Proc2X for Processor2
Proc3X for Processor3.
Go to the Performance Measures tab in the Experimenter window. From there:
Select Sink4 for the object and
Input for the statistic. To select the object
Sink4 in the object field or do the following:
Now that we've created the variables and performance measures, we'll set up some scenarios for our experiment.
Enter scenario names and values as follows:
Go to the Experiment Run tab. Hit the button. Each scenario will be run 5 times and the results of the Throughput performance measure will be collected at the end of each run. The status window will show which scenarios/replications are currently being run. FlexSim will run multiple scenarios simultaneously if your computer has a multi-core cpu.
Once the experiment is finished, click the button at the bottom. This will open a window where you can get data on the performance measures for the scenario. In this example we only have one performance measure, but if you had multiple you could see the results for each in this window. There are several options for how to display the data, including a Replications Plot, a Frequency Histogram, a Correlation Plot (for examining correlations between multiple performance measures), a Data Summary, and a Raw Data view.
In this experiment, the best scenario was the "Close" scenario, which averaged right around 99 parts of throughput. The worst scenario was the "Far Apart" scenario, which averaged about 75 parts throughput.
At this point, you've learned how to use the Experimenter. In the next tutorial task, you'll learn how to use the Optimizer. Continue on to Tutorial Task 4.2 - Optimizer.