Automated Meat Cut Quality Classification System
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Solution Overview
Problem
Manual inspection of meat cuts in retail environments is impractical and inconsistent, leading to variations in quality due to human error, making it difficult to ensure consistent high-quality cuts of meat.
Innovation Solution
An automated system comprising a capture device with an image capture device and depth sensor that captures and evaluates meat cuts against specifications, using machine learning to classify cuts and ensure quality, including thickness, trimming, and alignment, with a control circuit and database to store and retrieve specifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual inspection of meat cuts is performed, then quality evaluation can be conducted, but inconsistency and human error lead to variation in quality assessment
Solution Approach 1:
The patent replaces the manual mechanical inspection process with an automated imaging system that uses cameras and computer vision algorithms to evaluate meat cuts. The system captures images of meat cuts and uses image processing to objectively measure quality attributes such as color, texture, and dimensions, eliminating human subjectivity and inconsistency while maintaining reliable quality assessment.
2Reliability
If every cut of meat is examined manually, then quality can be ensured, but the process becomes impractical and time-consuming
Solution Approach 1:
The automated imaging system enables rapid inspection of meat cuts by capturing images and immediately processing them through computer vision algorithms. This allows the system to evaluate multiple cuts per minute, dramatically increasing productivity compared to manual inspection while ensuring comprehensive quality assurance of every cut.
Solution Approach 2:
The system creates digital copies of meat cuts through imaging, allowing quality evaluation to be performed on the image data rather than requiring physical handling and measurement of each cut. This copying approach enables rapid, non-contact inspection that maintains quality assurance while significantly improving throughput.
3Productivity
If multiple people divide primal cuts, then more cuts can be produced, but quality varies from person-to-person
Solution Approach 1:
The system provides objective feedback on cut quality by measuring specific attributes such as thickness, color, and texture against predetermined specifications. This feedback mechanism allows real-time monitoring and adjustment of cutting processes, ensuring that multiple workers can produce cuts of consistent quality by comparing their work against standardized criteria provided by the imaging system.
Solution Approach 2:
The patent uses the imaging system to objectively measure and control key parameters of meat cuts such as thickness, color intensity, and texture characteristics. By monitoring and adjusting these parameters, the system ensures consistent quality across cuts produced by different workers, transforming subjective quality assessment into objective parameter-based control.
Data Source
AI summary
In some embodiments, apparatuses and methods are provided herein useful to ensuring quality of meat cuts. In some embodiments, a system for ensuring quality of meat cuts comprises a capture device comprising an image capture device configured to capture an image of a cut of meat, a depth sensor configured to capture depth data, a transceiver configured to transmit the image and the depth data, a microcontroller configured to control the image capture device, the depth sensor, and the transceiver, a database configured to store meat cut specifications, and the control circuit configured to receive, from the capture device, the image and the depth data, retrieve, from the database, a meat cut specification, evaluate the image of the cut of meat and the depth data associated with the cut of meat, and classify the cut of meat.