Automated Defect Detection in Composite Package Sealing Bands
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Solution Overview
Problem
Current methods for evaluating the quality of sealings in composite packages, particularly transversal sealing bands, are labor-intensive, operator-dependent, and lack the ability for real-time, automated defect detection, leading to potential breaches in the packaging material and sterility issues.
Innovation Solution
An automated defect detection system utilizing a vision system with an imaging device and analysis unit, coupled with artificial intelligence and Polarsens CMOS image sensor technology, captures images of sealing bands during delamination, applying image processing algorithms and machine learning to detect defects like channels, burn marks, and plastic lumps, providing a confidence score and adjusting production parameters accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual inspection by technical operators is used to evaluate sealing quality, then the inspection can be performed with simple equipment, but the process is time-consuming and operator-dependent leading to inconsistent results
Solution Approach 1:
The patent replaces the manual mechanical inspection process with an automated vision system using imaging devices and image processing algorithms. The system captures images of sealing bands during delamination and uses automated defect detection to identify channels, burn marks, and plastic lumps, eliminating operator dependency and significantly reducing inspection time while maintaining or improving detection accuracy.
Solution Approach 2:
The vision system creates optical copies (images) of the sealing bands for analysis. Instead of physically examining the actual sealing with human eyes, the system captures and analyzes digital images, allowing for faster processing and consistent evaluation without the time constraints of manual inspection.
2Productivity
If manual inspection methods are used, then the equipment complexity remains low, but the extent of automation is insufficient leading to limited productivity
Solution Approach 1:
The patent implements an automated vision system that replaces manual inspection processes. The system includes imaging devices, image processing units, and automated defect detection algorithms that work together to inspect sealing bands continuously during production, significantly increasing inspection throughput despite the increased system complexity.
Solution Approach 2:
The system performs self-inspection by automatically capturing images, processing them through algorithms, and identifying defects without human intervention. The automated defect detection system evaluates sealing quality independently, enabling continuous high-speed inspection that improves productivity while the complexity is justified by the elimination of manual labor.
3Reliability
If automated vision systems with AI and Polarsens technology are implemented, then defect detection accuracy and automation extent improve, but the device complexity increases
Solution Approach 1:
The patent employs advanced automated vision systems with AI and Polarsens CMOS image sensor technology to replace manual inspection. These sophisticated systems provide reliable and consistent defect detection by analyzing optical properties of sealing bands, ensuring high sealing quality assurance despite the increased complexity of the automated system.
Solution Approach 2:
The system utilizes Polarsens technology to detect changes in optical parameters of the sealing material. By analyzing polarization and optical properties of the heat-seal plastic layers, the system can identify defects based on parameter variations, providing reliable quality assurance through precise measurement capabilities that justify the system complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system enables reliable, repeatable, and high-accuracy automated defect detection, reducing operator dependency and improving the efficiency of sealing inspection, ensuring consistent package quality and sterility.
Implementation Method 1
an imaging device configured to capture images of the sealing band
Implementation Method 2
Polarsens CMOS image sensor technology
Data Source
Figure 1~2
Figure 3~4
Figure 5~6
AI summary
There is described a system (1) for automated defect detection in sealing bands (2) of composite packages, each sealing band (2) being formed from a first band portion (3), a second band portion (4) and a layer of heat seal material (5) interposed between the first band portion (3) and the second band portion (4). The system (1) is provided with: a vision system (10) to capture images of the sealing band (2); and an analysis unit (12) operatively connected to the vision system (10) to analyze one or more images acquired by the vision system (10) to determine the quality of the sealing band (2) as a function of the one or more images. The analysis unit (12) has an artificial intelligence module (24) to analyze the one or more images by means of a machine-learning model, to detect the presence of defects in the sealing band (2).