This work presents a novel simulator that mimics a single machine sequencing problem. The simulator provides a dynamic and interactive platform for industrial engineering students to apply core disciplinary concepts, such as operations research, production planning, and optimization techniques, in the pursuit of finding optimal sequencing solutions. The implementation of this simulator in an industrial engineering course demonstrated its efficacy as an engaging and relevant pedagogical tool. Feedback collected from students revealed that the activity not only increased their interest and motivation but also significantly deepened their understanding of the complexities involved in sequencing problems. This study concludes that the use of such simulators in the classroom can greatly enhance the learning experience by making abstract concepts more tangible and by providing students with a hands-on approach to mastering difficult topics. The findings suggest that the incorporation of simulation-based activities into the curriculum is a valuable strategy for improving student outcomes in industrial engineering education.

In the field of industrial engineering, sequencing problems, particularly those involving single machines, are a fundamental area of study within operations research and production planning. These problems have significant real-world implications, as they directly impact the efficiency and productivity of manufacturing systems. A single machine sequencing problem typically involves determining the optimal order in which a set of jobs should be processed on a machine to minimize various objectives, such as total completion time, tardiness, or lateness. However, while the theoretical underpinnings of sequencing problems are well-covered in academic literature, students often struggle to grasp their practical complexities and applications.

One effective way to address this gap between theory and practice is using simulation-based learning activities. Simulators provide an interactive platform where students can apply their theoretical knowledge to realistic scenarios, fostering a deeper understanding of the material. Research has shown that simulation-based education enhances engagement, motivation, and comprehension by allowing students to experiment with complex systems in a risk-free environment. Moreover, simulators can effectively model real-world challenges, such as the variability and constraints encountered in production environments, making them ideal for teaching sequencing problems.

This article proposes a learning activity using a simulator that mimics a single machine sequencing problem, allowing students to apply core disciplinary content in a hands-on manner. The objective of this activity is not only to reinforce theoretical concepts but also to provide students with a tangible understanding of the difficulties in solving sequencing problems.

The simulator was implemented in an industrial engineering course, where students were tasked with finding an optimal sequencing solution for a set of jobs. Results of this study indicated that students found the activity engaging, relevant, and interesting, which in turn led to a deeper comprehension of the subject. This article outlines the need for simulation-based activities in industrial engineering education and presents the case for their inclusion as an effective method for bridging the gap between theoretical knowledge and practical application.

Keywords: Simulator, Machine sequencing, Educational innovation, Higher education, Industrial engineering.