A business process is a set of activities executed in a specific sequence involving various actors. This relationship between actors, activities, and sequence is crucial for achieving the goals and objectives of organizations. Business process modeling involves determining the actors, activities, and execution sequence necessary to accomplish the organization’s objectives, permitting analysis of the overall process in order to identify and rectify potential failures, improve operations, or eliminate activities that do not generate value. In this study, Petri nets have been selected as the modeling tool due to their ability to provide graphical and mathematical representations of business processes, which offers a significant advantage over other tools. The objective of this research is to develop a BP modeling algorithm using Petri nets. It aims to simulate the behavior of each activity within a case study in which the mathematical representation of Petri nets is utilized to measure process performance. Additionally, a software artifact is created to assess the algorithm’s functionality and compare the performance of two different business process that share the same goal.

El análisis de procesos de negocios (BP) investiga las propiedades de las entidades y atributos de dichos procesos, para ello, es necesario utilizar herramientas, estadísticas, análisis de tiempos y movimientos, simulación, minería de datos y obviamente la documentación del flujo de actividades. Puede ser representado gráficamente utilizando diferentes herramientas, por ejemplo, las redes de Petri (PN). Las PN permiten la representación de eventos combinando la visualización grafica con una notación matemática subyacente. El autor ha creado un algoritmo que convierte el texto de la descripción de un proceso de negocio en una red de Petri, y este ha sido programado en Python. En el presente artículo se describe el funcionamiento del mencionado algoritmo.