Development of a Vision-Based Color Sorting and Packaging System Using a 3-DOF Robotic Arm and PLC Control
DOI:
https://doi.org/10.59247/jfsc.v4i2.391Keywords:
Color Sorting, Siemens S7-1200 PLC, 3-DOF Robotic Arm, Machine Vision, Automated PackagingAbstract
Automated sorting and packaging play an important role in improving manufacturing productivity while reducing manual labor. An integrated automation platform for color sorting and packaging was designed and implemented by combining a three-degree-of-freedom (3-DOF) robotic arm, machine vision, and PLC-based control. Product images were acquired by a webcam for color recognition and position estimation, while system coordination was performed by a Siemens S7 1214 PLC controlling the conveyor, robotic arm, pneumatic capping mechanism, and supervisory functions. Real-time monitoring and basic operating functions were provided through an Android application communicating via the Modbus RTU protocol. Cycle testing demonstrated a theoretical capacity of 144 items per hour based on a 25-second processing duration and a 70% success rate. Parallel task scheduling in the PLC reclaimed approximately 2.5 seconds per run by removing idle delays between actuators. The physical rig brings together camera-based detection, PLC logic, robotic handling, and pneumatic tooling on one bench. Such performance benchmarks validate the design for academic experimentation and small-scale manufacturing.
References
J. M. Müller, O. Buliga, and K. I. Voigt, “Fortune favors the prepared: How SMEs approach business model innovations in Industry 4.0,” Technological Forecasting and Social Change, vol. 132, pp. 2–17, 2018, https://doi.org/10.1016/j.techfore.2017.12.019.
J. Werheid et al., “Machine vision in manufacturing SMEs: a review,” Discover Applied Sciences, vol. 7, no. 5, p. 371, 2025, https://doi.org/10.1007/s42452-025-06923-4.
S. R. Rallabandi, S. Yanda, C. J. Rao, B. Ramakrishna, and D. Apparao, “Development of a color-code sorting machine operating with a pneumatic and programmable logic control,” Materials Today: Proceedings, 2023, https://doi.org/10.1016/j.matpr.2023.05.150.
M. L. Dezaki, S. Hatami, A. Zolfagharian, and M. Bodaghi, “A pneumatic conveyor robot for color detection and sorting,” Cognitive Robotics, vol. 2, pp. 60–72, 2022, https://doi.org/10.1016/j.cogr.2022.03.001.
N. Almtireen et al., “PLC-Controlled Intelligent Conveyor System with AI-Enhanced Vision for Efficient Waste Sorting,” Applied Sciences (Switzerland), vol. 15, no. 3, p. 1550, 2025, https://doi.org/10.3390/app15031550.
H. I. Bozma and H. Yalçin, “Visual processing and classification of items on a moving conveyor: A selective perception approach,” Robotics and Computer-Integrated Manufacturing, vol. 18, no. 2, pp. 125–133, 2002, https://doi.org/10.1016/S0736-5845(01)00035-7.
K. R. Sughashini, V. Sunanthini, J. Johnsi, R. Nagalakshmi, and R. Sudha, “A pneumatic robot arm for sorting of objects with chromatic sensor module,” Materials Today: Proceedings, vol. 45, pp. 6364–6368, 2020, https://doi.org/10.1016/j.matpr.2020.10.936.
R. Mattone, G. Campagiorni, and F. Galati, “Sorting of items on a moving conveyor belt. Part 1: A technique for detecting and classifying objects,” Robotics and Computer-Integrated Manufacturing, vol. 16, no. 2, pp. 73–80, Apr. 2000, https://doi.org/10.1016/S0736-5845(99)00040-X.
I. Alrushidy, Y. Bahumid, R. Bin Shujaa, A. Abdullah, A. Kurd, and M. Abdullah, “Design and Fabrication of Color Sorting Machine Based on Computer Vision,” Journal of Science and Technology, vol. 30, no. 6, pp. 107–115, 2025, https://doi.org/10.20428/jst.v30i6.2954.
L. Fina, T. Mascarenhas, C. Smith, and H. Sevil, “Object Detection Accuracy Enhancement in Color based Dynamic Sorting using Robotic Arm,” in Florida Conference on Recent Advances in Robotics (FCRAR), 2023 https://doi.org/10.5038/cvse3872.
W. T. Abbood, O. I. Abdullah, and E. A. Khalid, “A real-time automated sorting of robotic vision system based on the interactive design approach,” International Journal on Interactive Design and Manufacturing, vol. 14, no. 1, pp. 201–209, 2020, https://doi.org/10.1007/s12008-019-00628-w.
J. Borrell, C. Perez-Vidal, and J. V. Segura, “Optimization of the pick-and-place sequence of a bimanual collaborative robot in an industrial production line,” International Journal of Advanced Manufacturing Technology, vol. 130, no. 9–10, pp. 4221–4234, 2024, https://doi.org/10.1007/s00170-023-12922-9.
X. Yang, Z. Zhou, J. H. Sørensen, C. B. Christensen, M. Ünalan, and X. Zhang, “Automation of SME production with a Cobot system powered by learning-based vision,” Robotics and Computer-Integrated Manufacturing, vol. 83, p. 102564, 2023, https://doi.org/10.1016/j.rcim.2023.102564.
J. Park, M. B. G. Jun, and H. Yun, “Development of robotic bin picking platform with cluttered objects using human guidance and convolutional neural network (CNN),” Journal of Manufacturing Systems, vol. 63, pp. 539–549, 2022, https://doi.org/10.1016/j.jmsy.2022.05.011.
X. Xiao, Y. Jiang, and Y. Wang, “Key Technologies for Machine Vision for Picking Robots: Review and Benchmarking,” Machine Intelligence Research, vol. 22, no. 1, pp. 2–16, 2025, https://doi.org/10.1007/s11633-024-1517-1.
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Kha-Vy Ngo, Hien-Dat Phan, Nguyen-Thanh-Phong Dang, Chi-Huy Lu, Quoc-Thinh Nguyen, Minh-Thang Vo, Binh-Hau Nguyen, Van-Tien Tran, Bao Pham, Long-Phi Pham, Nguyen-Duc-Duong Le, Quoc-Khanh Trinh, Tuan-Kiet Nguyen

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.