The university computer lab has 10 computers which are constantly being used by students. Users need help from the one lab assistant fairly often. Students ask for help at a Poisson rate of with an average of 4 requests per hour for any one computer. The assistant answers questions as quickly as possible and the service time follows an exponential distribution with mean of 1 minute per help session. The following queuing analysis spreadsheet was developed from this information.
72. What is the Kendall notation for this system?
73. Based on this report what is the probability that s student will not get instantaneous help?
74. Based on this report what is the average number of students waiting to be helped?
75. Based on this report how much time do students spend getting help before they can resume work on their computers?
A tax accountant has found that the time to serve a customer has a mean of 30 minutes (or 0.5 hours) and a standard deviation of 6 minutes (or 0.1 hours). Customer arrivals follow a Poisson distribution with an average of 60 minutes between arrivals. The following queuing analysis spreadsheet was developed from this information.
76. What is the Kendall notation for this system?
77. Based on this report what is the probability that a customer does not have to wait for assistance with his or her taxes?
78. Based on this report what is the average number of customers waiting to be helped?
79. Based on this report how long does a customer spend at the tax accountant’s office?
Internet Sales, Inc. is establishing a new ordering system to handle its on-line sales. Customers arrive randomly at an average of one every minute. On average it takes 45 seconds to process a customer’s order. The current system employs one network server to process orders. This server processes orders requests one at a time in the order received. The Internet Sales, Inc., Analysis Team has determined that customer orders arrive according to a Poisson process and the average time spent processing an order is exponentially distributed.
Internet Sales’ management knows that offering prompt, reliable on-line service is critical to their continued success. Upgrading the current on-line ordering capacity will establish their image as a “cutting edge” on-line sales company. On the other hand, too much unused capacity is inefficient and will ultimately cause company profits to decline.
Recently, the management group established a goal of serving an on-line customer immediately, 90% of the time. This means that 90% of the time a customer does net have to wait to place an order on-line after using the Internet Sales, Inc. web page. A heated discussion ensued over the current system’s capability of meeting this goal.
Under the current system, a customer waits if the system is busy processing another order. Network server upgrades are available in increments of $5000. Each upgrade adds the capability to process an additional order in parallel. For example if two upgrades were purchased at a cost of $10,000, order will be processed by three independent network servers each serving at an exponential rate of one order per 45 seconds. The Analysis Team was asked to consider the alternatives and recommend a course of action to the management group. What upgrade (if any) will meet the service goal set by the management group? What are the cost and performance trade-offs?
The university computer lab has 10 computers which are constantly being used by students. Users need help from the one lab assistant fairly often. Students ask for help at a Poisson rate of with an average of 4 requests per hour for any one computer. The assistant answers questions as quickly as possible and the service time follows an exponential distribution with mean of 1 minute per help session. The following queuing analysis spreadsheet was developed from this information.72. What is the Kendall notation for this system?73. Based on this report what is the probability that s student will not get instantaneous help?74. Based on this report what is the average number of students waiting to be helped?75. Based on this report how much time do students spend getting help before they can resume work on their computers?A tax accountant has found that the time to serve a customer has a mean of 30 minutes (or 0.5 hours) and a standard deviation of 6 minutes (or 0.1 hours). Customer arrivals follow a Poisson distribution with an average of 60 minutes between arrivals. The following queuing analysis spreadsheet was developed from this information.76. What is the Kendall notation for this system?77. Based on this report what is the probability that a customer does not have to wait for assistance with his or her taxes?78. Based on this report what is the average number of customers waiting to be helped?79. Based on this report how long does a customer spend at the tax accountant’s office?Internet Sales, Inc. is establishing a new ordering system to handle its on-line sales. Customers arrive randomly at an average of one every minute. On average it takes 45 seconds to process a customer’s order. The current system employs one network server to process orders. This server processes orders requests one at a time in the order received. The Internet Sales, Inc., Analysis Team has determined that customer orders arrive according to a Poisson process and the average time spent processing an order is exponentially distributed. Internet Sales’ management knows that offering prompt, reliable on-line service is critical to their continued success. Upgrading the current on-line ordering capacity will establish their image as a “cutting edge” on-line sales company. On the other hand, too much unused capacity is inefficient and will ultimately cause company profits to decline. Recently, the management group established a goal of serving an on-line customer immediately, 90% of the time. This means that 90% of the time a customer does net have to wait to place an order on-line after using the Internet Sales, Inc. web page. A heated discussion ensued over the current system’s capability of meeting this goal. Under the current system, a customer waits if the system is busy processing another order. Network server upgrades are available in increments of $5000. Each upgrade adds the capability to process an additional order in parallel. For example if two upgrades were purchased at a cost of $10,000, order will be processed by three independent network servers each serving at an exponential rate of one order per 45 seconds. The Analysis Team was asked to consider the alternatives and recommend a course of action to the management group. What upgrade (if any) will meet the service goal set by the management group? What are the cost and performance trade-offs?
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