The growth of the fast-food sector in Lima, driven by the demand for efficient and high-quality services, has created the need to optimize service times in these establishments. This study arises with the objective of addressing inefficiencies in service processes in a fast-food restaurant, using continuous improvement tools such as queuing theory, aggregate planning, and simulations with Arena software.

The research focused on improving order handling times through the standardization of methods and times, aggregate production planning, and the application of queuing theory. A continuous improvement model was developed in seven stages, which included detailed time and method studies, flow determination and time standards, and validation through simulations.

The most notable results included a significant reduction in average order handling times from 23.14 minutes to 19.18 minutes, which nearly doubled the total number of orders attended from 679 to 1,397. Additionally, the queue size and the number of customers leaving the line drastically decreased from 785 to 75 customers. Furthermore, revenues increased from 17,128 soles to 35,522 soles, demonstrating a remarkable improvement in operational efficiency and customer satisfaction. These indicators highlight the effectiveness of the proposed model in optimizing service times and increasing competitiveness in Lima's fast-food sector.

José Luis Sánchez-Flores

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Optimization of Service Times in Fast-Food Restaurants in Lima: Application of Continuous Improvement Tools and Process Simulation