Pilkington Library Simulation Study
Simulation Study
Pilkington Library Main Issuing Desk
Abstract: This paper investigates the activity of the main issuing desk at the 3rd floor of Pilkington Library during weekdays between 5 and 6pm. The aim is to find ways of minimizing queuing times and respond to flexibility in demand. Two sets of data have been analysed and transposed into a simulation study using the Simul8 software package. The results of the simulation are presented in support of our optimization proposals.
Introduction
With more than 370,000 books issued last year, serving almost 15,000 users which made up to 600,000 enquires, the Pilkington Library is definitely one of the busiest place on campus especially when it gets near the examination period.
One …show more content…
The only places where differences are noticeable are the maximum queuing time which has an error of about half a minute (2:52 min compared to the simulated 3.37 minutes). This might be explained by the modifications in efficiency which we made in order to reflect the fact that counters were closing from time to time because of the operator tacking another job (for example sorting returned books) or simply by tacking a break. However one of the two counters were permanently staffed at all time and we do not know whether the simulation considered this fact or not.
Efficiency for counter 1 has been set to 85% because there were times when the counter was closed. In the same way efficiency of the other working units have been altered in order to better reflect the reality. (i.e. self servicing machine 2 experienced software problems and it was out of order for most of the time)
Another adjustment we made to our simulation in order to best fit the real data was to set the inter-arrival and processing time in terms of our own designed distributions instead of using the classical built-in Exponential
Pilkington Library Main Issuing Desk
Abstract: This paper investigates the activity of the main issuing desk at the 3rd floor of Pilkington Library during weekdays between 5 and 6pm. The aim is to find ways of minimizing queuing times and respond to flexibility in demand. Two sets of data have been analysed and transposed into a simulation study using the Simul8 software package. The results of the simulation are presented in support of our optimization proposals.
Introduction
With more than 370,000 books issued last year, serving almost 15,000 users which made up to 600,000 enquires, the Pilkington Library is definitely one of the busiest place on campus especially when it gets near the examination period.
One …show more content…
The only places where differences are noticeable are the maximum queuing time which has an error of about half a minute (2:52 min compared to the simulated 3.37 minutes). This might be explained by the modifications in efficiency which we made in order to reflect the fact that counters were closing from time to time because of the operator tacking another job (for example sorting returned books) or simply by tacking a break. However one of the two counters were permanently staffed at all time and we do not know whether the simulation considered this fact or not.
Efficiency for counter 1 has been set to 85% because there were times when the counter was closed. In the same way efficiency of the other working units have been altered in order to better reflect the reality. (i.e. self servicing machine 2 experienced software problems and it was out of order for most of the time)
Another adjustment we made to our simulation in order to best fit the real data was to set the inter-arrival and processing time in terms of our own designed distributions instead of using the classical built-in Exponential