Run the model for 100 hours with 10 replication and goth the following result:
Run
Result
c <- 3 # Machine capacity
lambda <- 120 # Mean rate of arrival (lambda)
mu <- 50 # Mean service rate (mu)
rho <- lambda / (c * mu)
m <- c(0:(c-1))
p0 <- 1 / (sum((c * rho)^m / factorial(m)) + (c * rho)^c / (factorial(c) * (1- rho))) # Probability that there are 0 Steel plate in the system
L_q <- (p0 * (lambda / mu)^c * rho) / ((factorial(c) * (1 - rho)^2)) # Mean number of Steel plate in the queue
L <- L_q + lambda / mu # Mean number of Steel plate in the system
W_q <- L_q / lambda # Mean wait in the queue
W <- W_q + 1 / mu # Mean wait in the system
\(W_q\) = 0.021573
\(W\) = 0.041573
\(L_q\) = 2.588764
\(L\) = 4.988764
\(\rho\) = 0.8
We get almost the same results for sumulation and theoritcal.