Sealing Section Quality Assessment Using Optical Imaging
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Solution Overview
Problem
Current methods for quality assessment of sealing sections in food packages are time-consuming and inefficient, requiring manual inspection or indirect pressure tests to detect insufficient sealing, which can lead to delays and increased costs.
Innovation Solution
A method and apparatus using image capture and processing to identify sealing section features, such as distance measures, boundary deviations, and non-sealed areas, by comparing captured image data with reference features, allowing for automated assessment of sealing quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual inspection or indirect pressure tests are used to detect insufficient sealing, then sealing quality can be assessed, but time and effort required for quality control increases
Solution Approach 1:
The patent replaces manual inspection and indirect pressure tests with direct optical imaging and image processing. A camera captures images of the sealing section, and image processing algorithms automatically analyze sealing quality by detecting features such as sealing lines, gaps, and defects. This substitution of mechanical/manual methods with optical and computational methods enables rapid, automated assessment without time-consuming manual intervention or complex pressure testing apparatus.
Solution Approach 2:
The patent creates an optical copy (image) of the sealing section and analyzes this copy to assess sealing quality. Instead of physically testing the seal or manually examining it, the system captures an image of the sealing section and processes this visual copy to identify sealing defects, measure sealing dimensions, and determine seal integrity. This copying approach enables non-contact, rapid assessment that eliminates time losses associated with physical testing or manual inspection.
2Productivity
If automated image processing is implemented for sealing assessment, then time and effort for quality control is reduced, but device complexity increases
Solution Approach 1:
The patent introduces an intermediary image processing system that bridges the simple camera capture and the complex sealing quality assessment. The image processing algorithms serve as an intermediary layer that automatically extracts relevant features (sealing lines, gaps, defects) from raw images and translates them into quality metrics. This intermediary processing reduces the complexity burden on the overall system by automating the analysis step, making the device more manageable while maintaining high productivity.
Solution Approach 2:
The image processing system performs self-service by automatically analyzing sealing quality without requiring manual intervention or complex external testing equipment. The system captures images, processes them through algorithms that identify sealing features and defects, and generates quality assessments autonomously. This self-service capability increases productivity while keeping device complexity manageable, as the system handles its own analysis rather than requiring additional complex testing apparatus or manual operations.
Data Source
AI summary
A method for quality assessment of a sealing section of a package, wherein the package includes at least a robustness layer and a plastic layer. The sealing section is formed by holding a first section and a second section of the package against each other while providing heat such that the plastic layer of the first and second section melt and thereby provide for that the first and second section adhere to each other. The method includes capturing image data depicting the sealing section using a camera, identifying a reference line in the image data, identifying a sealing section boundary line in the image data, determining a sealing section assessment feature set based on the reference line and the sealing section boundary line, and comparing the sealing section assessment feature set with a reference feature set.