Food Object Processing with Automated X-Ray Inspection and Segmentation
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Solution Overview
Problem
The existing methods for processing food objects, such as fish fillets, are inefficient as they require the entire object to be rejected if an undesired object is detected, leading to excessive handling and reduced throughput due to manual rework processes.
Innovation Solution
A method that utilizes image data, such as X-ray data, to dynamically determine cutting patterns and automatically separate smaller food pieces containing undesired objects, allowing only those pieces to be rejected and processed, thereby enhancing throughput and minimizing material handling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the entire food object is rejected when an undesired object is detected, then food safety is ensured, but throughput is reduced and material waste increases
Solution Approach 1:
The food object is divided into multiple smaller portions through automated cutting, and only the portions containing undesired objects are rejected while safe portions are kept. This segmentation allows selective rejection rather than whole-object rejection, maintaining food safety while improving throughput and reducing material waste.
Solution Approach 2:
The undesired objects (bones, bloodspots, gapings, nematodes) are identified and extracted from the food object through imaging detection. By taking out only the contaminated portions rather than rejecting the entire object, the system ensures food safety while maximizing usable material recovery and throughput.
2Measurement precision
If manual inspection and rework processes are used to find undesired objects, then detection accuracy is achieved, but time consumption increases and throughput decreases
Solution Approach 1:
Manual inspection and rework processes are replaced with an automated system combining imaging equipment (X-ray or visible light cameras) and computer-controlled cutting devices. This substitution maintains high detection accuracy for undesired objects while dramatically reducing time consumption through automated operation, thereby increasing throughput.
Solution Approach 2:
The imaging detection and cutting operations are performed automatically during the conveyance process before the food object leaves the processing line. This preliminary automated action eliminates the need for subsequent manual inspection and rework, reducing time loss while maintaining detection accuracy.
3Reliability
If excessive handling of raw material is performed during rejection and recirculation, then quality control is maintained, but processing efficiency decreases
Solution Approach 1:
The system performs self-inspection through imaging equipment and self-cutting through automated cutting devices, eliminating the need for manual handling, rejection, and recirculation operations. This self-service approach maintains quality control by automatically identifying and removing contaminated portions while significantly improving processing efficiency by minimizing handling time.
Solution Approach 2:
The cutting operation is performed continuously during the conveyance process without stopping the production line. By maintaining continuous useful action rather than interrupting for manual inspection and handling, the system preserves quality control through automated detection while maximizing processing efficiency.
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
This approach increases processing efficiency by allowing continuous conveyance and cutting of food objects without whole-object rejection, reducing rework time and material waste, and enabling precise identification and removal of undesired objects using robotic or conveyor systems.
Implementation Method 1
said image data comprises X-ray data obtained by means of exposing the food object with an X-ray beam and processing the intensities of the X-ray beam after penetrating through the food object
Data Source
Figure 1
Figure 2~4
AI summary
This invention relates to method of processing a food object while the food object is being conveyed, comprising acquiring image data of the food object (101), cutting the food object into smaller food pieces (102), determining, based on the acquired image data, whether the food object contains undesired objects (103), and in case such undesired objects are detected, identifying which of the smaller food pieces contain the undesired objects (104).