DSME Lecture 4
Ideally, in waiting line or queuing analysis, we want to balance the cost of service capacity with the cost of waiting.
. TRUE A central problem in many service settings is the management of waiting time. The manager must weigh the added cost of providing more rapid service (more traffic lanes, additional landing strips, more checkout stands) against the inherent cost of waiting.
An infinite population in waiting line management refers to a population that is large enough in relation to the service system so that the change in population size caused by subtractions or additions to the population does not significantly affect the system probabilities
TRUE An infinite population is large enough in relation to the service system so that the population size caused by subtractions or additions to the population (e.g., a customer needing service or a serviced customer returning to the population) does not significantly affect the system probabilities.
A finite population in waiting line management refers to a population that is large enough in relation to the service system so that the change in population size caused by subtractions or additions to the population does not significantly affect the system probabilities.
FALSE A finite population refers to the limited-size customer pool that will use the service and, at times, form a line. The reason this finite classification is important is that when a customer leaves its position as a member for the population (e.g., a machine breaking down and requiring service), the size of the user group is reduced by one, which reduces the probability of the next occurrence.
"Combine the pain" is an application of behavioral science to service encounters. It means that, when something is going wrong for a group of customers, it is better to totally enrage one or a very few customers rather than slightly annoying a large number of customers.
FALSE Events seem longer when they are segmented. This suggests that we want to break pleasant experiences into multiple stages and combine unpleasant ones into a single stage.
In a department, 25 machines are kept running by three operators who respond to randomly occurring equipment problems. An analyst wanting to know whether to add a fourth operator or downsize to two operators would be helped by using queuing theory analysis.
TRUE Finite source population: Whereas the infinite queueing models assume a large population, finite queuing employs a separate set of equations for those cases where the calling customer population is small. In this problem, operators, must service 25 machines to keep them operating. Based on the costs associated with machines being idle and the costs of operators to service them, the problem is to decide how many operators to use. And, given that there are three operators, you can estimate the down time and thus lost production. Then you can estimate the downtime and lost production for a shift with only two operators. If the difference between these two results is smaller than the pay of one operator, you can downsize. If not, you can calculate the difference in downtime for four operators, compute the difference between three and four operators and, if the difference is great enough, hire a fourth operator.
An important aspect of service products is that they cannot be inventoried.
TRUE In designing service organizations, we must remember one distinctive characteristic of services: We cannot inventory services.
A variable arrival rate is more common in waiting line management than a constant arrival rate
TRUE In productive systems, the only arrivals that truly approach a constant interval period are those subject to machine control. Much more common are variable (random) arrival distributions.
