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Design and Implementation of Automatic Palletizing System with Vision Based Algorithms for Quality Control | IEEE Conference Publication | IEEE Xplore

Design and Implementation of Automatic Palletizing System with Vision Based Algorithms for Quality Control


Abstract:

In recent years, the pharmaceutical industry has been implementing automatic systems in their manufacturing and packaging processes. This has led to reduced risks, increa...Show More

Abstract:

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.
Date of Conference: 15-17 September 2023
Date Added to IEEE Xplore: 30 November 2023
ISBN Information:
Conference Location: Nanjing, China

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