ETFCam - a Multifunctional Didactic Model for Machine Vision and Automated Visual Inspection

This paper presents the development and implementation of a flexible industrial machine model for automated visual inspection, called ETFCam, designed to improve the learning outcomes of electrical engineering students in the field of machine vision and robotics. Unlike prefabricated didactic models, which are typically “closed” systems with a predefined set of experiments, custom didactic systems for teaching and training built from scratch tend to be more flexible and provide a deeper insight in engineering, machine design and planning, while being more cost-effective. The proposed system is based on a 3DOF stepper motor-based manipulator, a DC motor driven conveyor, a pneumatic actuated gripper and a machine vision system. The paper discusses several applications of such a system in an educational environment, with a special focus on machine vision applications. Due to the fact that the system is versatile, open, modular, and easy to upgrade, it has unlimited potential and possibilities for further development. In addition, it provides students with a perfect testbed for learning new engineering skills in many areas such as schematic drawing and understanding, PLC based control, sensing, and machine vision.

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Publication Details

Published
2024-09-16
DOI
https://doi.org/10.1109/elmar62909.2024.10694039
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
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article

ETFCam - a Multifunctional Didactic Model for Machine Vision and Automated Visual Inspection

Samim Konjicija, Emir Sokić, Nedim Osmić, Almir Salihbegović et al.
Industrial Vision Systems and Defect Detection
article

ETFCam - a Multifunctional Didactic Model for Machine Vision and Automated Visual Inspection

Samim Konjicija, Emir Sokić, Nedim Osmić, Almir Salihbegović, Majda Curtic-Hodzic
article en

Abstract

This paper presents the development and implementation of a flexible industrial machine model for automated visual inspection, called ETFCam, designed to improve the learning outcomes of electrical engineering students in the field of machine vision and robotics. Unlike prefabricated didactic models, which are typically “closed” systems with a predefined set of experiments, custom didactic systems for teaching and training built from scratch tend to be more flexible and provide a deeper insight in engineering, machine design and planning, while being more cost-effective. The proposed system is based on a 3DOF stepper motor-based manipulator, a DC motor driven conveyor, a pneumatic actuated gripper and a machine vision system. The paper discusses several applications of such a system in an educational environment, with a special focus on machine vision applications. Due to the fact that the system is versatile, open, modular, and easy to upgrade, it has unlimited potential and possibilities for further development. In addition, it provides students with a perfect testbed for learning new engineering skills in many areas such as schematic drawing and understanding, PLC based control, sensing, and machine vision.

University of Sarajevo (BA)
Openalex Percentile: Top 76%
Industrial Vision Systems and Defect Detection
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