Parts arrive at a two-machine system according to an exponential interarrival distribution with mean 20 minutes. upon arrival, the parts are sent to machine 1 and processed. the processing-time distribution is tria (4.5, 9.3, 11) minutes. the parts are then processed at machine 2 with a processing-time distribution as tria (16.4, 19.1, 20.8) minutes. the parts from machine 2 are directed back to machine 1 to be processed a second time (same processing-time distribution but an independent draw from it). the completed parts then exit the system. run the simulation for a single replication of 20,000 minutes to observe the average number in the machine queues and the average part cycle time with arena model

the answer   is 200

step-by-step explanation:

this is a problem about poisson probabilities.   i don't know if you've

already studied poisson distributions, or if you have a place to look

to read more about the subject.  

here's how you can see a poisson distribution coming.   when there are

a lot of events that may happen at any time (or any place), and when

you're counting how many of them happen at a particular time (or a

particular place), and each event is independent of the others, then

the result is a poisson distribution.   this is roughly true for the

chocolate chips; one chip being in a cookie has only a small effect on

the probability that another chip will be in the cookie.

once you know you have a poisson distribution, you know a lot.   there

is only one parameter to a poisson distribution, so if you know the

mean, you know everything.   the form of the distribution is

  probability of n chips = {[e^(-x)]*(x^n)} / (n! )

7.25

step-by-step explanation:

we know that 7 equals to 7.0. we also know that 1/4=0.25. so we can add the two together and we get 7.25

maya’s expression will generate the wrong sum because she violated the commutative property.

step-by-step explanation: