Concept explainers
a)
Interpretation: probabilities of no customer in 5 mins.
Concept introduction: Poisson arrivals are a reasonably good assumption for unscheduled systems. Further if there is a mix of many different types of jobs the exponential distribution can be realistic for service times. Otherwise it tends to be too variable of a distribution.
b)
Interpretation: probabilities of exactly one customer in a min.
Concept introduction: Poisson arrivals are a reasonably good assumption for unscheduled systems. Further if there is a mix of many different types of jobs the exponential distribution can be realistic for service times. Otherwise it tends to be too variable of a distribution.
c)
Interpretation: probabilities of exactly two customers in 2mins.
Concept introduction: Poisson arrivals are a reasonably good assumption for unscheduled systems. Further if there is a mix of many different types of jobs the exponential distribution can be realistic for service times. Otherwise it tends to be too variable of a distribution.
d)
Interpretation: probability of at least two customers in 10 mins.
Concept introduction: Poisson arrivals are a reasonably good assumption for unscheduled systems. Further if there is a mix of many different types of jobs the exponential distribution can be realistic for service times. Otherwise it tends to be too variable of a distribution.
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Production and Operations Analysis, Seventh Edition
- A cafeteria serving line has a coffee urn from which customers serve themselves. Arrivals at the urn follow a Poisson distribution at the rate of 2.0 per minute. In serving themselves, customers take about 25 seconds, exponentially distributed. (a) How long would you expect it to take to get a cup of coffee, including waiting time? (b) If the cafeteria installs an automatic vendor that dispenses a cup of coffee at a constant time of 25 seconds, how long would you expect it to take (in minutes) to get a cup of coffee, including waiting time?arrow_forwardBBA Bank (a fictitious one) has a drive-through teller window and observed that 15 customers arrive for service per hour, on an average, and the average service time per customer is 3 minutes. Assume inter-arrival time and service time follow a negative Exponential distribution. The bank hires you as a consultant. You guess that this is an M|M|1 system and you are required to determine the following: Probability (teller is busy) Probability (teller is idle) Probability of 3 customers in the system. Average number of customers waiting for service, that is, number of autos in the line excluding the one at the teller window. Average number of customers in the system, that is, number of autos in the line including the one at the teller window. Average time a customer spends in the system, that is, waiting time plus service time. Average time a customer spends in the waiting line before reaching the teller window.arrow_forward
- Practical Management ScienceOperations ManagementISBN:9781337406659Author:WINSTON, Wayne L.Publisher:Cengage,