Hi group and Raymond.
My name is Rainer Uwe Bode and I work in Brazil at a consulting firm. I do
SD modeling since 1996.
I have been accompanying this discussion for the last two weeks, and I must
say that in case I had some certainties before, they are all gone now.
If a process converts a single object at a time,
> it is a discrete-event process. If the process works on a continuous
> stream, it is a continuous process. If a system is composed of one or
> discrete-event processes, it must be a discrete-event system. If a system
> is composed of one or more continuous processes, it must be a continuous
So, if you have pieces on an assembly line, lets say bars of steal,
managing one at a time, you willl have, accordingly, discrete time events.
But, if you convert all the bars into weight and process them at tons/ hour,
you will have a continuous process in continuous time.
So, the same event can be addressed and modeled in two different ways.
Then, the problem is not the one-at-a-time, since you can convert almost all
intire units into averaged pieces processed continuously, like envelopes.
The problem in deciding what method to use seems more to be one of deciding
wether you want to accompany the variations of a stream of items, or if you
want to accompany a single object from start to finish.
So, if you want to see, in a set of bars, bar 37 travel through the system,
you would want to use a discrete-event-modeling.
If tou prefer to analyse the journey of the bundle of bars, the bottlenecks
and the supply-chain, SD would be more than adequate.
Still, the specs of the flow of time seem to be of minor importance when
comparing dicrete and SD modeling: to me, the basic criterium for choice
seems to be the necessity of considering the more complex phenomena, like
feedbacks and non-linearities.
To me, with SD ou are able to address a lot more broader spectrum of
problems, whereas discrete-event-modeling seems to be useful in a more
Rainer Uwe Bode