Pallet Container Classification via Infrared Imaging
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Solution Overview
Problem
Manual counting and classification of folded plastic supermarket boxes on pallets are prone to human errors, costly, and inefficient, especially when the volume is high, and existing automation solutions do not effectively address the issue of detecting discrepancies in box numbers and types before the pallet is returned.
Innovation Solution
A device comprising a conveying belt, infrared and visible light radiation means, and image acquisition systems that surround the pallet to classify containers without unwrapping them, using data analysis to identify alphanumeric codes, contours, and colors, with machine learning algorithms for improved accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual counting and classification is used, then the process is simple and low-cost, but human errors increase and productivity decreases
Solution Approach 1:
The patent replaces the manual mechanical counting and classification system with an automated optical inspection system. The system uses radiation means (infrared and visible light sources) and image acquisition means (cameras) to capture images of containers on pallets, eliminating the need for manual visual inspection. This substitution increases both productivity by automating the process and reliability by providing consistent, error-free detection of container characteristics.
Solution Approach 2:
The system creates optical copies (images) of the containers using radiation means and image acquisition means. These images are then analyzed by data analysis means to extract information about container characteristics such as color, shape, and alphanumeric codes. This copying approach enables automated classification without physical contact with the containers, improving both speed and accuracy.
2Productivity
If automation is implemented with unwrapping and separating boxes, then productivity increases, but device complexity and cost increase
Solution Approach 1:
The patent extracts only the essential function needed for classification - visual inspection - from the complete automation process. Instead of implementing a complex system that unwraps, separates, and inspects each box individually, the system extracts the inspection function and applies it to the pallet as a whole through optical means. This reduces device complexity while maintaining automation benefits.
Solution Approach 2:
The optical inspection system serves multiple functions simultaneously: it captures images of all containers on the pallet, detects various container characteristics (color, shape, codes), and provides data for classification. This multi-functional approach eliminates the need for separate mechanisms for each inspection task, reducing overall system complexity while maintaining high productivity.
3Loss of time
If inspection is performed after the pallet is returned, then the process is simple, but time loss increases and discrepancies are detected late
Solution Approach 1:
The system performs inspection at the moment the pallet arrives at the facility, before the containers are distributed or used. This preliminary inspection detects any discrepancies in container numbers, types, or conditions immediately upon receipt, allowing for timely correction or notification. The automated optical system enables this early detection without adding significant complexity to the receiving process.
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
Automates the classification process, reducing human error and costs by accurately counting and identifying box types and models through image analysis, enabling immediate detection of discrepancies and improving the efficiency of box inspection and return processes.
Implementation Method 1
a plurality of first radiation means suitable for emitting light in the infrared spectrum
Implementation Method 2
a plurality of second radiation means suitable for emitting light in the visible spectrum
Implementation Method 3
a plurality of first image acquisition means suitable for obtaining images and/or data in the infrared spectrum, a plurality of second image acquisition means suitable for obtaining images in the visible spectrum
Data Source
Figure 1
Figure 2a~2b
Figure 3a~3b
AI summary
The invention provides a device (1) for containers classification, comprising a first structure (3) and data analysis means (6). The first structure (3) comprises first radiation means (41) suitable for emitting light in the infrared spectrum and first image acquisition means (51) suitable for obtaining images and/or data in the infrared spectrum. The data analysis means (6) is adapted to analyze the images and/or data obtained by the first image acquisition means (51) and providing a classification of the containers (11) piled on the pallet (10). The first image acquisition means (51) have motion means configured to move at least part of the first image acquisition means (51) from a first position where the first image acquisition (51) means allow the platform or pallet (10) enter the first structure and a second position where the first image acquisition means (51) surround the platform or pallet (10). The invention also provides a method for containers classification.