Vision-Guided Food Block Cutting for Exact-Weight Bars
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Solution Overview
Problem
Conventional food cutting systems produce significant waste and giveaway when converting large blocks of cheese into smaller portions, with inefficiencies resulting in 15% waste and 1% giveaway, while aiming for exact weight individual bars.
Innovation Solution
A conveyor system integrated with a camera vision system and programmable logic controller that creates a 3D image of the food block, determines an optimized cut solution, and controls cutting operations to minimize waste and maximize yield, achieving less than 10% waste and ½% giveaway, with stations for cutting, weighing, trimming, and aligning bars for equal weight.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If conventional multi-stage cutting operation is used to cut blocks into smaller portions, then cutting process is simple and straightforward, but waste increases to 15% and giveaway increases to 1% over target weight
Solution Approach 1:
The system performs preliminary scanning and 3D imaging of the food block before cutting to create a digital model. This allows the optimization algorithm to plan the cutting pattern in advance, identifying the maximum number of bars meeting weight specifications before any physical cutting occurs, thereby minimizing waste and giveaway.
Solution Approach 2:
The patent replaces conventional mechanical cutting systems with a vision-guided system that uses cameras to scan the food block, creates a 3D model, and uses software optimization to determine cut patterns. This substitution of mechanical sensing with optical sensing enables precise measurement and optimization that reduces waste.
2Productivity
If conventional cutting system is used, then equipment construction is simple and inexpensive, but productivity and yield maximization are compromised with only 85-90% suitable bars produced
Solution Approach 1:
The system incorporates feedback through camera scanning that captures the actual dimensions and shape of each food block. This real-time data feeds into the optimization algorithm, which adjusts the cutting pattern for each individual block to maximize yield. The feedback loop ensures that each cut is optimized based on actual measured parameters rather than predetermined patterns.
Solution Approach 2:
The optimization algorithm dynamically changes cutting parameters such as cut positions, angles, and patterns based on the scanned 3D model of each food block. By varying these parameters according to the specific geometry and density distribution of each block, the system maximizes the number of suitable bars produced from each block.
3Manufacturing precision
If conventional cutting system is used, then manufacturing cost is low, but manufacturing precision deteriorates with significant giveaway over target weight
Solution Approach 1:
The patent replaces simple mechanical cutting with a vision-guided system that uses optical sensing to precisely measure block dimensions and density. This substitution enables precise control of cut positions to achieve target weights within tight tolerances (less than 0.5% giveaway) while maintaining cost-effectiveness through software-based optimization rather than complex mechanical adjustments.
Solution Approach 2:
The system performs preliminary scanning and weight calculation before cutting, allowing it to plan cut positions that will produce bars within the target weight specification. This pre-planning ensures manufacturing precision by determining optimal cut locations based on the actual block characteristics rather than relying on fixed mechanical guides.
Data Source
AI summary
A system for cutting blocks of food product into bars of substantially equal weight. The system includes a cutter conveyor configured to receive incoming blocks of food product and move the blocks along an in-line processing path in a plane for cutting; a programmable logic controller coupled to the cutter conveyor; and, multiple stations associated with the cutter conveyor. One such station is a camera vision system configured to create an image of the slab portion, and further including a camera controller coupled to the vision system and the PLC, and configured to determine an optimized cut solution of the slab portion from the image and data related to the food product, and is configured to provide the cut solution to the PLC. The PLC is configured to control the cutting of the food product, based on the optimized cut solution, into bars of substantially equal weight.