So on average, there is 1 television set in the shop?

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SUMMARY

The discussion revolves around a repairman servicing broken televisions, where the repair time follows an exponential distribution with a mean of 20 minutes, and broken sets arrive at a rate of 12 per 8-hour workday. The analysis identifies the system as an M/M/1 queuing model, calculating the fraction of time the repairman is busy as 2/3, indicating he has work to do 66.67% of the time. The mean put-through time, which includes waiting and repair time, is derived using specific queuing theory formulas. The average number of televisions in the shop is confirmed to be 1, based on the traffic density calculations.

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Homework Statement


A repairman fixes broken televisions. The repair time is exponentially distributed with a mean of 20 minutes. Broken television sets arrive at his shop according to a Poisson process with arrival rate 12 sets per working day. (8 hours).
(i) What is the fraction of time that the repairman has work to do?
(ii) What is the mean put-through time (waiting time plus repair time) of a television?
(iii) How many television sets, on average, in his shop?

2. The attempt at a solution
Mean arrival rate = 12/8 hours = 12/480 minutes = 0.025 minutes
Mean servicing time = 20 minutes

So:
\lambda = 3/2 = Arrival Rate
\mu = 1/(1/3) = 3 = Service Rate
\rho = (3/2)/(3) = 1/2 = Traffic Density

(i) - Fraction of time that the repairman has work to do.
I'm basing all this on my assumption that it's an M\M\1 queuing system. So the fraction of time which repairman has no work to do is 1 - the average time per customer, T?

T = N/\lambda = 1/(\mu - \lambda) so, 1/(3 - 3/2) = 2/3? So 1/3 of his time he has no work to do?

(ii) - Mean throughput time:
Average waiting time:
\rho/(\mu(1-\rho)) + 1/\mu

(iii) - \rho/1-\rho = (0.5)/(0.5) Which is 1...
 
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I think your theory is incorrect. You seem to be using formulae for an infinite and continuous queue.
 
Ok, thanks for the advice.

Any ideas on what formulas I should be using?
 

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