I'm looking to use a monte carlo distribution on the number of workers per workstation. Currently I have multiple workers working at a single workstation. The data collected is a small sample size (we have a reasonable idea of the worst case scenario and best case scenario) so I was looking for a way to weight what is the most likely number of workers vs what can actually happen. I know the Monte Carlo distribution is a way to randomly generate a lot of points quickly, however, I do not know if Plant Sim has this sort of distribution or another way to model this. Any thoughts would be appreciated!
if you need a random integer you can use the following SimTalk code in Plant Simulation 13:
var n:integer := z_uniform(1,1,11)
You will receive a number from 1 to 10.
Plant Simulation 12
local n:integer := z_uniform(1,1,11)
If you have observed numbers with frequencies you can use the Primitive Empirical distribution.
Please look at the documentation (index z_emp).
If you can describe your problem more precisely, we can possibly offer a solution without programming.
Thanks for the response. So in the current state a part takes a couple weeks to be processed, completed, and on to the next workstation. The number of workers also varies day by day over those weeks. Typically a bell curve of workers over that span (start with a couple workers then by the middle of the process there's about 20 workers working and then at the end back down to a couple workers). Is there any part of plant simulation that accounts for a variability of workers of a processing time or even a way to code this?
For example, a part would be worked on for 4 weeks. The first week they have 4 workers, second week they have 8 workers, third week they have 9 workers, and fourth week they would have 5 workers. This is all completed at the same workstation. Is there a way to model this flucuation of workers?