Treffer: Integrating Python and Microsoft Excel in teaching parametric optimization in Process Engineering ; Integrando Python y Microsoft Excel en la enseñanza de la optimización paramétrica en Ingeniería de Procesos ; Integrando Python e Microsoft Excel no ensino de otimização paramétrica em Engenharia de Processos

This study presents a teaching methodology for parametric optimization in a Chemical Engineering class at the Federal University of Rio Grande do Norte (Brazil), using Microsoft Excel and Python. The methodology was organized into three progressive phases. In the first, a questionnaire was applied to assess the students' prior knowledge. In the second, more realistic optimization problems were discussed in class, highlighting the limitations of traditional analytical approaches and presenting the basic functionalities of the tools adopted. In the final phase, students were challenged to solve a complex optimization problem involving a network of heat exchangers, using the two tools mentioned. Although 57.14% of the students opted for non-computerized analytical methods in the questionnaire proposed in the initial phase, the problem in the final phase was successfully solved, resulting in a score of 8.0 in the numerical assessment. This reflects the success of the intervention carried out during phase 2, guided by the results obtained in phase 1 of the research. Python and Excel have proven to be effective tools for teaching parametric optimization, even in small and heterogeneous classes. ; Este estudio presenta una metodología de enseñanza de la optimización paramétrica en una clase de Ingeniería Química de la Universidad Federal de Rio Grande do Norte (Brasil), utilizando Microsoft Excel y Python. La metodología se organiza en tres fases progresivas. En la primera, se aplica un cuestionario para evaluar los conocimientos previos de los estudiantes. En la segunda, se discuten en clase problemas de optimización más realistas, destacando las limitaciones de los enfoques analíticos tradicionales y presentando las funcionalidades básicas de las herramientas adoptadas. En la fase final, los estudiantes se enfrentan al reto de resolver un problema complejo de optimización que implique una red de intercambiadores de calor, utilizando las dos herramientas mencionadas. A pesar de que el 57,14% de los alumnos optaron por ...