Apply labels in your 3D model

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In FlexSim, a label is a means of assigning data or information to flow items, tokens, or 3D objects in your model.

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Labels enable you to create distinctions between entities, so that you can dynamically control how your model operates.

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For example, you can use labels to make decisions based on the object type,

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to record statistics for items that flow through a specific part of the process, or to restrict how a token operates.

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Once applied, labels are an important component of building the logic of a model.

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A label has three elements that need to be considered:

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The label owner is the flow item, token, or 3D object that the label is assigned to.

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In this example, the owner is the Box.

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The label name is a descriptor for the type of information the label includes and should be easily identifiable.

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In this example, there are three labels—Type, Weight, and SerialNumber.

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As a best practice, do not include spaces in label names, keep label names short and recognizable,

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and begin labels with a capital letter.

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Following these recommendations makes it easier to reference labels in your model.

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Additionally, FlexSim prioritizes capitalized attributes, which means that labels with capital letters appear first in auto-fill options.

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Finally, the label value is the information, or the actual data point, that you are storing.

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In this example, the Type of the Box is set to a numerical integer of 1.

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Other boxes might be labeled with a 2 or 3 to differentiate between types.

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Here, notice that the Weight label is not set to a specific unit, and might refer to pounds, ounces, or kilograms.

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It is up to you to determine how you will use and interpret labels in the logic and statistics of your model,

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so you can set the label up in any way that makes sense to you.

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Lastly, the SerialNumber in this example is a set of alphanumeric characters, or a string.

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Labels can include text, numbers, strings, references to other objects, and other types of data.

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Next, review how to apply a label.

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In the Model shown, items enter through the Source into Queue1, then the Operator takes them to the Processor.

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Here, 60% of the items are set to flow to the Sink, and 40% of the items will travel back to the Queue for rework.

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Watch as the model is Run.

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In this example, there is no way to record the items that return to the Queue.

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To solve this issue, you can use a Trigger that sets a Label based on the path of the item.

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In the Model, select Processor1.

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In Properties, under Triggers, click Add a new Trigger, and select On Exit.

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Click Add/Edit this Trigger’s operations, then select Data > Set Label.

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In the Set Label properties, set the Object you are assigning the trigger to—in this case, the item.

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Next, give the Label a name—here, “ReworkState”.

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Then, assign a value—in this case, port.

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This label is set to equal the port that the item flows to, 1 or 2.

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Reset and Run the model.

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As you encounter an item that requires rework, Stop the simulation.

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Then, in the Model, click the item.

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In Properties, under Labels, note that the item has a ReworkState label of 2.

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Run the model again and select the item when it finishes reprocessing.

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The label is reassigned a 1, because the item now flows to Port 1—the Sink.

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In this example, you can now gather statistics using the label.

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Select the Dashboard pane, where a table displays the total output of the objects.

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In the Library, under Output, select Output by Type.

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Select the Bar Chart, then drag and drop it onto the Dashboard.

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In Properties, under Objects, click the Sampler, and in the Model, select the Processor.

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Then, change the Type Label to “ReworkState” to differentiate by this Label.

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Note that this field is case sensitive and needs to match the Label name exactly.

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You can verify the Label name under Triggers, in the Set Label Properties.

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Back in the Bar Chart Properties, leave the remaining selections set to the defaults.

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Reset and Run the simulation.

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Now, the model uses the label to record how many items travel via Port 1 and Port 2.

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If you speed the model up, you can see that the bar chart more clearly displays the expected 60/40 split between ports 1 and 2.

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Labels are a means of assigning data that helps to differentiate objects, tokens,

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and flow items in your model, allowing you to effectively build model logic and to gather meaningful statistics to evaluate your model.