TY - GEN
T1 - Design and Implementation of Automatic Palletizing System with Vision Based Algorithms for Quality Control
AU - Arce, Diego
AU - Pérez-Zuñiga, Gustavo
AU - Flores, Edelfre
AU - Cuellar, Francisco
AU - Jimenez, Victor
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - In recent years, the pharmaceutical industry has been implementing automatic systems in their manufacturing and packaging processes. This has led to reduced risks, increased productivity, lower costs, and improved competitiveness. The adoption of Industry 4.0 principles and technologies has played a key role in automating processes and optimizing results. Therefore, this paper presents the design, implementation, and preliminary validation of an automatic palletizing and quality control system implemented in the solid drug production line. The proposed system incorporates two main technologies: intelligent computer vision and collaborative robotics, which are complemented with industrial-grade equipment and instruments. The computer vision system performs quality control on pallet boxes by detecting defects, tears, stains, and taping faults on each side of the boxes, as well as recognizing the text characters of the labels for subsequent processing. Additionally, a weight-based quality control is implemented to ensure that all boxes contain the exact number of solid drugs. Through preliminary validation tests, the viability of using this automated mechatronic system for the handling and quality control of boxes was demonstrated. The handling process was carried out using a robot, and it was determined that the robot can complete palletizing and quality control of a pallet of 21 boxes in a total of 11 minutes and 33 seconds. This innovative solution represents a successful application of Industry 4.0 principles and technologies in the pharmaceutical industry, enabling companies to further optimize their processes and remain competitive in the market.
AB - In recent years, the pharmaceutical industry has been implementing automatic systems in their manufacturing and packaging processes. This has led to reduced risks, increased productivity, lower costs, and improved competitiveness. The adoption of Industry 4.0 principles and technologies has played a key role in automating processes and optimizing results. Therefore, this paper presents the design, implementation, and preliminary validation of an automatic palletizing and quality control system implemented in the solid drug production line. The proposed system incorporates two main technologies: intelligent computer vision and collaborative robotics, which are complemented with industrial-grade equipment and instruments. The computer vision system performs quality control on pallet boxes by detecting defects, tears, stains, and taping faults on each side of the boxes, as well as recognizing the text characters of the labels for subsequent processing. Additionally, a weight-based quality control is implemented to ensure that all boxes contain the exact number of solid drugs. Through preliminary validation tests, the viability of using this automated mechatronic system for the handling and quality control of boxes was demonstrated. The handling process was carried out using a robot, and it was determined that the robot can complete palletizing and quality control of a pallet of 21 boxes in a total of 11 minutes and 33 seconds. This innovative solution represents a successful application of Industry 4.0 principles and technologies in the pharmaceutical industry, enabling companies to further optimize their processes and remain competitive in the market.
KW - Automation
KW - Computer Vision
KW - Mechatronics
KW - Palletizing
KW - Quality Control
UR - http://www.scopus.com/inward/record.url?scp=85181536198&partnerID=8YFLogxK
U2 - 10.1109/ICRCV59470.2023.10329106
DO - 10.1109/ICRCV59470.2023.10329106
M3 - Conference contribution
AN - SCOPUS:85181536198
T3 - 2023 5th International Conference on Robotics and Computer Vision, ICRCV 2023
SP - 271
EP - 277
BT - 2023 5th International Conference on Robotics and Computer Vision, ICRCV 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th International Conference on Robotics and Computer Vision, ICRCV 2023
Y2 - 15 September 2023 through 17 September 2023
ER -