Simulating daily customer demand

Hello everybody,

I would like to discuss a general topic on how to simulate daily customer demands.
In my model, the ordered material is pulled from a supermarket with multiple conveyors for the specific item numbers. In detail I realized this by opening the output ports through a couple of messages coming from reoccurring UserEvents and closing them after the daily amount has been released and counted.

Now the problem is that it might not be realistic that the same amount is ordered every day OR if you have a 'calculated' demand of e.g. 6.3 FlowItems per day, you have to think about a way to model 0.3 FlowItems somehow.

I thought about 2 ways.

Idea 1: Use 10 different UserEvents and 10 different table values (e.g. pull 6 FlowItems on 7 days and 7 FlowItems on 3 days -> equal average of 6.3 Flowitems/day)

Idea 2: Use a probability distribution function and round it to an integer, the pull amount will vary, but the advantage will be correct over time. I built a sample model (see attachment) and I'm quite happy with the result.

I used the following code:

round(exponential(gettablenum("abruf",1,1)-1,1

Note: 'abruf' means 'demand' in German



In the screenshot you can see the pull amount I specified in the experimenter and the results on the right hand side.

What do you think about the ideas and have you had similar problems or alternative approaches?

Thanks in advance!
Jens

You could take a separate source and sink to bild a customer demand takt. Set the arrival time to whatever you want, and send on exit trigger a message to your queue to releas the flowitem.