Queuing Analysis The Study of Student’s Admission System at Rajamangala University of Technology Phra Nakhon, North Bangkok Campus

Abstract

The objectives of the study were to find the arrival rate of applicants who applied to study at Rajamangala of Technology Pra Nakhon, North Bangkok Campus, the service rate of admission officers, and to analyze queuing system in order to improve the admission system. The sample was 1,722 technical students who applied to study in 10 divisions in 2007 and 2008. The plication date was collected every 10 minutes in each one-hour period from 09.00 am. to 16.00 pm. For 6 days. The study found that the distribution of the number of applicants was Poisson distribution. The highest arrival rate, 1.29 student/min, was at the second period and the lowest arrival rate, 0.06 students/min, was at the sixth period. The Distribution of service time at each station was exponential distribution. The highest service rate, 0.67 min/student or 1.49 students/min, was at the second station, entering data into a computer. Queuing analysis in this study was series network. The analysis found that the highest expected number of applicants in the system, 150 student/hour, was at the first station in the second period, and in the sixth period there was almost none. The highest expected number of applicants in the queuing system,107.40 student/hour, was at the first station in the second period, The highest expected waiting time in the system.1.92 min/student and in the queuing system, 1.37 min/student were at the first station. The probabilities of none of applicants in the system at the first, the second and the third station in the sixth period were high, 0.97, 0.95, and 0.98 respectively. The proper value of the expected number of applicants in the system set in this study was not more than 60 student/hour and not less than 30 student/hour. The proper value of the waiting time in the system was not more than 1 min/student and not less than 0.5 min/student for stations for stations with more than one servers. The analysis found that at the first station one more server should be added in the second, the third and the forth period, and one less server should be reduced in the sixth period.