Apply the M/M/C Model of Queuing Theory in a Service System Based on FlexSim Simulation in the Post-COVID

Abstract

The study includes a literature review, modeling and simulation concepts, applications, FlexSim characterization, and the M/M/C model, i.e., multiple channels. Customer service processes with Coronavirus Disease 2019 (COVID-19) have been affected by dissimilar reasons among them the distancing that causes queues to become longer and the set of operations to be carried out with the same personnel, being this a not so satisfactory experience for the customer. The article addresses key concepts related to the use of FlexSim software within a simulation model in a service process where decisions can be made based on the study of queuing theory. After performing the Poisson goodness-of-fit test, it was determined that the distribution of hourly queue arrivals does meet a Poisson-type distribution since its Chi-square test reaches a value of 0.92 which is well above the coefficient of 0.5. Therefore, the exact probability of finding n arrivals during a given time T can be found, if the process is random, as is the case of the cooperative. The average number of customers in the queue waiting to be served, gives a reduction from 1.04 to 0.14 customers, so it is understood that, if the increase of servers in the cooperative were applied, this would cause queues to be generated in the system, since its L_q is 0.14 customers.