The issue with the experimenter settings.

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liam asked Aug 13, '24 Logan Gold commented Aug 29, '24

The issue with the experimenter settings.

Hi,

I have some questions regarding the experimenter. In my model, there is a MultiProcessor with five subprocesses, and I have set the standard deviation of the processing time for each subprocess as variables (aaa, bbb, ccc, ddd, eee). These variables range from 0 to 1 to represent the proportion of variation.

In Scenario 1 of the experimenter, I set all five variables to 0, indicating that there should be no variation in the processing time for these subprocesses.

However, the experimental results show that when I set the replications per scenario to 20, there is still variation in the processing time.

I would appreciate your guidance on how to resolve this issue. Thank you very much for your assistance.

fifo.fsm

Software Version:

FlexSim 22.2.0

variable processortime experimentor

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fifo.fsm (1.7 MiB)

· 2

Jason Lightfoot ♦♦ commented · Aug 21 at 04:17 PM

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Logan Gold ♦♦ commented · Aug 29 at 02:16 PM

Hi @liam, was Felix Möhlmann's answer helpful? If so, please click the "Accept" button at the bottom of their answer. Or if you still have questions, add a comment and we'll continue the conversation.

If we haven't heard back from you within 3 business days we'll auto-accept an answer, but you can always comment back to reopen your question.

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Answer 1 · 2024-08-22T06:08:50Z

Felix Möhlmann answered Aug 22, '24

The parameters currently don't do anything. You have to add code to their On Set trigger that actually sets the global variables' value.

That being said, you don't really need the global variables. You can just use the parameters directly in the process time code.

Model.parameters.aaa*Table("DIP_order")[item.Order_ID][7]

I would also like to add that using the mean value as the standard deviation in a normal distribution will regularly give you a processing time of 0, which doesn't seem realistic. Maybe a different distribution (for example triangular) is better suited.

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