Abstract:

The teaching of graphic representation techniques has evolved significantly from an approach traditionally centered on mastering standardized plans to encompassing the complexity of three-dimensional representation. This evolution is closely linked with advancements in software and new geomatics technologies, such as laser scanning, which facilitate the digitization of objects and scenes. Consequently, these advancements have profoundly impacted pedagogical approaches in this field. Currently, computer-aided design (CAD) technologies are integrated into the teaching of graphic representation techniques. This perspective aligns with the expectations of companies, where proficiency in CAD software is considered essential for professional competitiveness. Therefore, this article aims to present a teaching-learning methodology that enables students to replicate real-world challenges they will encounter in their professional lives, particularly focusing on the skill of reverse engineering, which is highly valued in the industry.

Reverse engineering is a process frequently employed by companies to obtain geospatial information from data collected by various geomatic sensors, enabling the precise reconstruction of parts or components. This methodology not only prepares students for their future careers as engineers but also equips them with practical skills and a deeper understanding of key concepts in graphic representation.

The proposed teaching-learning methodology is organized into two distinct stages. The initial phase begins with the creation, or downloading for a public repository, of CAD models of individual parts or components, selected by the professor to modulate the activity's difficulty level. These CAD models are then transformed into synthetic point clouds, simulating the digitization process using geomatic sensors. The synthetic point clouds can simulate varying degrees of spatial resolution and incorporate Gaussian noise of different magnitudes to enhance the realism of the simulation, as each geomatic sensors has different technical specifications. This approach eliminates the necessity of performing digitization with actual geomatic sensors, thereby facilitating the instructor's task and accommodating the specific circumstances of each course. The resulting point cloud is not an exact replica of the theoretical model, requiring students to apply critical thinking and normalization knowledge to identify the theoretical geometry of the part/component rather than merely relying on the point cloud.

In the second stage, during the course instruction, students are provided with the synthetic model and tasked with generating the CAD model from the point cloud using the concepts learned in class. This core activity challenges students to discern the design constraints of the part that are not immediately apparent in the point cloud. Through this exercise, students gain a comprehensive understanding of the design process and are encouraged to engage in autonomous learning by applying a range of theoretical concepts to practical scenarios. The feedback acquired from this activity guides students in overcoming challenges and improving their ability to achieve more accurate results.

Overall, this methodology aims to bridge the gap between theoretical knowledge and practical application, thereby enhancing the educational experience and better preparing students for the demands of the professional world.

Keywords:

Computer-Aided Design (CAD), Reverse engineering, Geomatics, Engineering Education.