Vol. 5 No. . Especial (2025): Rhombus
ARTICLE

Application of Queueing Models and Simulation to Evaluate the Efficiency of the Ice Cream Service at McDonald’s Chapinero

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  • Gabriela Zipaquira,
  • Laura Sofia Guerrero,
  • Francy Rocio Castellanos
Gabriela Zipaquira
0009-0009-2734-7358
DOI: https://doi.org/10.63058/rhombus.v5iEspecial.340

Published 2025-10-28

Keywords

  • Queueing theory,
  • Simulation,
  • Waiting time,
  • Operational efficiency,
  • Optimization

How to Cite

Zipaquira, G., Guerrero, L. S., & Castellanos, F. R. (2025). Application of Queueing Models and Simulation to Evaluate the Efficiency of the Ice Cream Service at McDonald’s Chapinero. Rhombus, 5(. Especial), 21p – 48p. https://doi.org/10.63058/rhombus.v5iEspecial.340

Copyright (c) 2025 Rhombus

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Abstract

McDonald's is a globally recognized fast-food chain known for operational efficiency and standardized processes. In Chapinero, Bogotá, a specialized ice cream outlet was established, strategically located in a busy commercial and student area with high pedestrian traffic. This outlet, focused on products such as McFlurrys, cones, and sundaes, initially experienced long queues and extensive wait times, prompting this research. The study aimed to analyze and optimize the operational performance of the outlet using advanced industrial engineering techniques and artificial intelligence. Real data on customer arrival and service times were collected and statistically analyzed to identify the distribution that best represented these times, determining the Gamma distribution as the most suitable. Subsequently,
computational simulations were performed using Python and FlexSim to evaluate critical indicators such as average waiting time, service rate, and system saturation levels. These simulations provided clear visualization of internal processes, identified bottlenecks, and facilitated the exploration of alternative operational scenarios.
Finally, the analysis led to concrete improvement proposals related to installed capacity, efficient personnel allocation, and optimal task distribution based on actual demand. These changes significantly reduced wait times and substantially enhanced service efficiency and customer experience.

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