Improving customer waiting time for medicine-retrieval center
Fecha
2021-04-12
Autores
Plazas Escudero, David
Cárdenas-Rodríguez, Juan Sebastian
Restrepo Sierra, Mateo
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Editor
Universidad Eafit
Resumen
Neuromedica is a Colombian pharmacy which provides treatment for people with neurological diseases. Recently, Neuromedica started attending patients from other pharmacy which led to a significant increase in the waiting time. In this pharmacy, people are classified and attended due to certain priorities. The data,
given by Neuromedica, is analyzed using boxplots, Kruskal-Wallis and Kolmogorov-Smirnov tests with Python’s library Scipy. The objective of this work is to determine the number of assistants and queue logistic such that the waiting time has a significant reduction, with the purpose to provide a satisfactory level of service. A discrete-event simulation model was created and implemented in Python. A heuristic approach to minimize the waiting time is used. Additionally, a sensitivity analysis is made on the assumed distributions.