Development of an integrated industrial classification and control system with machine vision and PLC automation
DOI:
https://doi.org/10.24054/rcta.v2i48.4390Keywords:
robotics, artificial vision, PLCAbstract
This article presents the design and implementation of a prototype for the identification, manipulation, and transport of objects, aimed at simulating an industrial process for classification and quality control. The system integrates a robotic arm, the YOLO detection model, ArUco markers, a PLC-controlled conveyor module, and 3D-printed figures, programmed primarily in Python. The methodology consisted of developing each system separately and then integrating them into a single graphical interface. The robotics and machine vision segments were developed entirely in Python; the PLC was programmed in TIA Portal and connected to Python using Snap7. System evaluation involved repeatability tests for manipulation and transport, and measurements were taken of the YOLO model's classification and segmentation accuracy, as well as the accuracy of the ArUco markers.
Downloads
References
H. Lasi, P. Fettke, H. G. Kemper, T. Feld, and M. Hoffmann, “Industry 4.0,” Business and Information Systems Engineering, vol. 6, no. 4, pp. 239–242, Aug. 2014, Accessed: Aug. 26, 2025. [Online]. Available: http://dx.doi.org/10.1007/s12599-014-0334-4
J. Werheid et al., “Machine vision in manufacturing SMEs: a review,” Discover Applied Sciences, vol. 7, no. 5, pp. 1–23, May 2025, Accessed: Aug. 26, 2025. [Online]. Available: https://doi.org/10.1007/s42452-025-06923-4
N. Hutten, M. Alves Gomes, F. Holken, K. Andricevic, R. Meyes, and T. Meisen, “Deep Learning for Automated Visual Inspection in Manufacturing and Maintenance: A Survey of Open- Access Papers,” Applied System Innovation, vol. 7, no. 1, p. 11, Jan. 2024, Accessed: Aug. 26, 2025. [Online]. Available: https://doi.org/10.3390/asi7010011
A. Bin Rashid and M. A. K. Kausik, “AI revolutionizing industries worldwide: A comprehensive overview of its diverse applications,” Hybrid Advances, vol. 7, Dec. 2024, doi: 10.1016/J.HYBADV.2024.100277.
J. T. Licardo, M. Domjan, and T. Orehovacki, “Intelligent Robotics—A Systematic Review of Emerging Technologies and Trends,” Electronics (Basel)., vol. 13, no. 3, Jan. 2024, Accessed: Jun. 18, 2026. [Online]. Available: https://doi.org/10.3390/electronics13030542
R. Ben Ruben, C. Rajendran, R. Saravana Ram, F. Kouki, H. M. Alshahrani, and M. Assiri, “Analysis of barriers affecting Industry 4.0 implementation: An interpretive analysis using total interpretive structural modeling (TISM) and Fuzzy MICMAC,” Heliyon, vol. 9, no. 12, p. e22506, Dec. 2023, Accessed: Aug. 26, 2025. [Online]. Available: https://doi.org/10.1016/j.heliyon.2023.e22506
J. Ekong, V. Chauhan, J. Osedeme, S. A. Niknam, and R. Nguyen, “A framework for Industry 4.0 workforce training through project-based and experiential learning approaches,” ASEE Annual Conference and Exposition, Conference Proceedings, Aug. 2022, Accessed: Aug. 26, 2025. [Online]. Available: https://peer.asee.org/a-framework-for-industry-4-0-workforce-training-through-project-based-and-experiential-learning-approaches.pdf
B. Salah, S. Khan, M. Ramadan, and N. Gjeldum, “Integrating the Concept of Industry 4.0 by Teaching Methodology in Industrial Engineering Curriculum,” Processes, vol. 8, no. 9, p. 1007, Aug. 2020, Accessed: Aug. 26, 2025. [Online]. Available: https://doi.org/10.3390/pr8091007
A. Bondin and J. P. Zammit, “Education 4.0 for Industry 4.0: A Mixed Reality Framework for Workforce Readiness in Manufacturing,” Multimodal Technologies and Interaction, vol. 9, no. 5, p. 43, May 2025, Accessed: Jun. 18, 2026. [Online]. Available: https://doi.org/10.3390/mti9050043
I. Ahmad et al., “Inclusive learning using industry 4.0 technologies: addressing student diversity in modern education,” Cogent Education, vol. 11, no. 1, Dec. 2024, Accessed: Jun. 18, 2026. [Online]. Available: https://doi.org/10.1080/2331186X.2024.2330235
M. Ryalat, N. Almtireen, G. Al-refai, H. Elmoaqet, and N. Rawashdeh, “Research and Education in Robotics: A Comprehensive Review, Trends, Challenges, and Future Directions,” Journal of Sensor and Actuator Networks, vol. 14, no. 4, p. 76, Jul. 2025, Accessed: Jun. 18, 2026. [Online]. Available: https://doi.org/10.3390/jsan14040076
M. Vukovic, O. Jorg, M. Hosseinifard, and G. Fantoni, “Low-Cost Digitalization Solution through Scalable IIoT Prototypes,” Applied Sciences, vol. 12, no. 17, p. 8571, Aug. 2022, Accessed: Jun. 18, 2026. [Online]. Available: https://doi.org/10.3390/app12178571
B. Ismaili, S. Bakkali, and S. Benriyene, “The Employability of Engineers in the Era of Industry 4.0,” Engineering Proceedings, vol. 97, no. 1, p. 35, Jun. 2025, Accessed: Aug. 26, 2025. [Online]. Available: https://doi.org/10.3390/engproc2025097035
D. N. Ege, J. R. Johannessen, S. E. Kildal, C. V. Amundsen, M. F. Berg, and M. Steinert, “Successfully Prototyping Industry 4.0 for Adoption in Smes: Guidelines and Case Study on a Low-Cost Vision-Based Measurement Systems for Slate Manufacturing,” Jul. 2024, Accessed: Aug. 26, 2025. [Online]. Available: https://dx.doi.org/10.2139/ssrn.4884856
M. E. Latino, “A maturity model for assessing the implementation of Industry 5.0 in manufacturing SMEs: learning from theory and practice,” Technol. Forecast. Soc. Change, vol. 214, May 2025, Accessed: Jun. 18, 2026. [Online]. Available: https://doi.org/10.1016/J.TECHFORE.2025.124045
M. Mikhail and W. Sealy, “Configuration of a PLC Controlled Articulated Robot for Autonomous Vision Inspection Applications,” LACCEI International Multi-Conference for Engineering, Education, and Technology, no. 1, Jun. 2022, Accessed: Jun. 18, 2026. [Online]. Available: http://dx.doi.org/10.18687/LACCEI2022.1.1.347
M. Maslanka, D. Jancarczyk, and J. Rysinski, “Integration of Machine Vision and PLC-Based Control for Scalable Quality Inspection in Industry 4.0,” Sensors, vol. 25, no. 20, Oct. 2025, Accessed: Jun. 18, 2026. [Online]. Available: https://doi.org/10.3390/s25206383
Y. Li, P. Lai, T. Yang, and Z. Li, “Design and development of a machine-vision-based positioning compensation system for industrial robots,” Discover Applied Sciences, vol. 8, no. 2, pp. 174-, Dec. 2025, Accessed: Jun. 18, 2026. [Online]. Available: https://doi.org/10.1007/s42452-025-08196-3
M. Ayaida, N. Messai, F. Valentin, and D. Marcheras, “TalkRoBots: A Middleware for Robotic Systems in Industry 4.0,” Future Internet, vol. 14, no. 4, Mar. 2022, Accessed: Jun. 18, 2026. [Online]. Available: https://doi.org/10.3390/fi14040109
B. Dafflon, N. Moalla, and Y. Ouzrout, “The challenges, approaches, and used techniques of CPS for manufacturing in Industry 4.0: a literature review,” The International Journal of Advanced Manufacturing Technology, vol. 113, no. 7, pp. 2395–2412, Feb. 2021, Accessed: Jun. 18, 2026. [Online]. Available: https://doi.org/10.1007/s00170-020-06572-4
V. Fonseca, R. Barbosa, and F. Pereira, “Interoperability in Industrial Robotics: A Literature Review and Conceptual Path Toward a Universal Robot Protocol,” Applied Sciences, vol. 16, no. 11, May 2026, Accessed: Jun. 18, 2026. [Online]. Available: https://doi.org/10.3390/app16115217
J. S. Nieto Solano and S. A. Toro Mendoza, “Desarrollo de una interfaz gráfica interactiva para el robot OpenBotv V1 en el entorno de MATLAB,” Universidad Distrital Francisco José de Caldas, 2022. Accessed: Jul. 09, 2025. [Online]. Available: http://hdl.handle.net/11349/30190
G. A. Yerbabuena Torres, “Diseño e implementación de una interfaz de comunicación para el control de posición de un brazo robótico de forma local y remota,” Escuela Politécnica Nacional, 2024. Accessed: Jul. 10, 2025. [Online]. Available: http://bibdigital.epn.edu.ec/handle/15000/25344
C. A. Valdiviezo Romero and R. A. Valladares Yanqui, “Implementación de un robot humanoide con reconocimiento de objetos por color y forma,” Universidad Politécnica Salesiana, 2023. Accessed: Jul. 10, 2025. [Online]. Available: http://dspace.ups.edu.ec/handle/123456789/24123
C. Chronis and I. Varlamis, “FOSSBot: An Open Source and Open Design Educational Robot,” Electronics (Basel)., vol. 11, no. 16, Aug. 2022, Accessed: Jun. 18, 2026. [Online]. Available: https://doi.org/10.3390/electronics11162606
J. Vega and V. Pérez, “G-ARM: An open-source and low-cost robotic arm integrated with ROS2 for educational purposes,” Multimed. Tools Appl., vol. 84, no. 33, Mar. 2025, Accessed: Jun. 18, 2026. [Online]. Available: https://doi.org/10.1007/s11042-025-20748-8
R. J. Trute, C. S. Zapico, A. Christou, D. Layeghi, S. Craig, and M. S. Erden, “Development of a Robotic Surgery Training System,” Front. Robot. AI, vol. 8, Jan. 2022, Accessed: Jun. 18, 2026. [Online]. Available: https://doi.org/10.3389/frobt.2021.773830
J. Vega and J. M. Cañas, “Open Vision System for Low-Cost Robotics Education,” Electronics (Basel)., vol. 8, no. 11, Nov. 2019, Accessed: Jun. 18, 2026. [Online]. Available: https://doi.org/10.3390/electronics8111295
J. Vega and J. M. Cañas, “PiBot: An Open Low-Cost Robotic Platform with Camera for STEM Education,” Electronics (Basel)., vol. 7, no. 12, Dec. 2018, Accessed: Jun. 18, 2026. [Online]. Available: https://doi.org/10.3390/electronics7120430
D. L. Moreira Ramos, “Aplicación de un modelo de reconocimiento de objetos utilizando Yolo (you only look once),” Universidad Estatal Península de Santa Elena, 2021. Accessed: Jul. 09, 2025. [Online]. Available: https://repositorio.upse.edu.ec/handle/46000/5755
X. Jiménez Gómez, “Detección y análisis de datos sobre especies exóticas en biomas diferenciados en apoyo a la biodiversidad empleando la herramienta YOLO y microcontroladores,” Universidad de La Coruña, 2024. Accessed: Jul. 09, 2025. [Online]. Available: http://hdl.handle.net/2183/39543
A. Schcolnik-Elias, S. Martínez-Díaz, J. E. Luna-Taylor, and I. Castro-Liera, “Detección de armas tipo pistola mediante el uso de redes convolucionales con una arquitectura tipo YOLO y estereoscopía,” Pädi Boletín Científico de Ciencias Básicas e Ingenierías del ICBI, vol. 11, pp. 196–204, Sep. 2023, Accessed: Jul. 09, 2025. [Online]. Available: https://doi.org/10.29057/icbi.v11iEspecial2.10727
M. Liaqat Ali, Z. Zhang, S. Tomassini, and M. Ali Akber Dewan, “The YOLO Framework: A Comprehensive Review of Evolution, Applications, and Benchmarks in Object Detection,” Computers, vol. 13, no. 12, Dec. 2024, Accessed: Jun. 17, 2026. [Online]. Available: https://doi.org/10.3390/computers13120336
P. Mittal, “A comprehensive survey of deep learning-based lightweight object detection models for edge devices,” Artif. Intell. Rev., vol. 57, no. 9, pp. 242-, Aug. 2024, Accessed: Jun. 17, 2026. [Online]. Available: https://doi.org/10.1007/s10462-024-10877-1
W. Y. Feng, Y. F. Zhu, J. T. Zheng, and H. Wang, “Embedded YOLO: A Real-Time Object Detector for Small Intelligent Trajectory Cars,” Math. Probl. Eng., vol. 2021, no. 1, Jan. 2021, Accessed: Jun. 17, 2026. [Online]. Available: https://doi.org/10.1155/2021/6555513
P. Vilcapoma et al., “Comparison of Faster R-CNN, YOLO, and SSD for Third Molar Angle Detection in Dental Panoramic X-rays,” Sensors, vol. 24, no. 18, Sep. 2024, Accessed: Jun. 17, 2026. [Online]. Available: https://doi.org/10.3390/s24186053
B. Karacaoglu and M. E. Sahin, “Optimized YOLO architectures for efficient Kiwi detection in precision agriculture on embedded systems,” Sci. Rep., vol. 15, no. 1, Dec. 2025, Accessed: Jun. 17, 2026. [Online]. Available: https://doi.org/10.1038/s41598-025-32770-9
M. C. Luculescu, L. Cristea, A. Laszlo Boer, M. Gupta, F. I. Tiberiu Petrescu, and L. M. Ungureanu, “Artificial Vision System for Autonomous Mobile Platform Used in Intelligent and Flexible Indoor Environment Inspection,” Technologies (Basel)., vol. 13, no. 4, Apr. 2025, Accessed: Jun. 18, 2026. [Online]. Available: https://doi.org/10.3390/technologies13040161
F. D. Romero Herrera, “Diseño e implementación de un sistema de control y monitoreo de parámetros eléctricos dentro de procesos industriales mediante software libre y comunicación Modbus,” Escuela Superior Politécnica de Chimborazo, 2022. Accessed: Jul. 07, 2025. [Online]. Available: https://dspace.espoch.edu.ec/handle/123456789/17704
W. A. Fernández Lojano and D. F. Idrovo Vazconez, “Desarrollo de un sistema de monitoreo y control remoto para un variador de frecuencia Delta integrado a un PLC S7-1200 de Siemens por medio de una pasarela Inteligente basado en Raspberry Pi,” Universidad Politécnica Salesiana del Ecuador, 2024. Accessed: Jul. 08, 2025. [Online]. Available: http://dspace.ups.edu.ec/handle/123456789/27554
D. Macko, L. Hrmo, J. Hrbcek, and P. Nagy, “Real-Time Control System for Model Railway Based on SIMIS W Interlocking System,” Applied Sciences, vol. 15, no. 1, Dec. 2024, Accessed: Jun. 18, 2026. [Online]. Available: https://doi.org/10.3390/app15010180
D. Ionescu et al., “Communication and Control of an Assembly, Disassembly and Repair Flexible Manufacturing Technology on a Mechatronics Line Assisted by an Autonomous Robotic System,” Inventions, vol. 7, no. 2, Jun. 2022, Accessed: Jun. 18, 2026. [Online]. Available: https://doi.org/10.3390/inventions7020043
Q. T. Dao, L. T. Nguyen, T. K. Ha, V. H. Nguyen, and T. A. Nguyen, “Investigation of Secure Communication of Modbus TCP/IP Protocol: Siemens S7 PLC Series Case Study,” Applied System Innovation, vol. 8, no. 3, Jun. 2025, Accessed: Jun. 18, 2026. [Online]. Available: https://doi.org/10.3390/asi8030065
F. J. Folgado, D. Calderón, I. González, and A. J. Calderón, “Review of Industry 4.0 from the Perspective of Automation and Supervision Systems: Definitions, Architectures and Recent Trends,” Electronics (Basel)., vol. 13, no. 4, Feb. 2024, Accessed: Jun. 18, 2026. [Online]. Available: https://doi.org/10.3390/electronics13040782
M. Barton, R. Budjac, P. Tanuska, I. Sladek, and M. Nemeth, “Advancing Small and Medium-Sized Enterprise Manufacturing: Framework for IoT-Based Data Collection in Industry 4.0 Concept,” Electronics (Basel)., vol. 13, no. 13, Jun. 2024, Accessed: Jun. 18, 2026. [Online]. Available: https://doi.org/10.3390/electronics13132485
G. Caiza and R. Sanz, “An Immersive Digital Twin Applied to a Manufacturing Execution System for the Monitoring and Control of Industry 4.0 Processes,” Applied Sciences, vol. 14, no. 10, May 2024, Accessed: Jun. 18, 2026. [Online]. Available: https://doi.org/10.3390/app14104125
Robotics 4.0, “E-Robotics 4.0.” Accessed: Jun. 19, 2026. [Online]. Available: https://robotics40.com/e-robotics-4-0/
DYNAMIXEL, “AX-12A.” Accessed: Aug. 29, 2025. [Online]. Available: https://emanual.robotis.com/docs/en/dxl/ax/ax-12a/
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Diego Alejandro Landinez Quintero, Francisco Ernesto Moreno García, Wlamyr Palacios Alvarado
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
