Cold-Chain Quality Coding for Product-Sensitive Perishable Monitoring
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing perishable product monitoring systems fail to incorporate both product and transportation quality into a comprehensive metric, leading to inefficiencies and increased food waste due to temperature abuses in the cold chain.
Innovation Solution
A system and method using sensors and deep learning tools to generate a quality code that objectively quantifies temperature management and handling from harvest to destination, incorporating cut-to-cool time, transportation quality, and remaining shelf life, with an alphanumeric code (ANQC) that combines multiple indicators of product quality in a compact format.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional monitoring systems are used to track temperature in the cold chain, then temperature data can be collected, but the systems fail to provide a comprehensive quality metric that incorporates both product and transportation quality
Solution Approach 1:
The patent combines multiple quality indicators (product quality, transportation quality, temperature management quality) into a single comprehensive quality code. This merging of information sources resolves the contradiction by providing complete quality information without requiring multiple separate monitoring systems, thus reducing overall system complexity while preventing information loss.
Solution Approach 2:
The quality code system serves multiple functions: it monitors temperature, assesses product quality, evaluates transportation quality, and provides a unified metric for decision-making. This multi-functionality resolves the contradiction by consolidating various monitoring tasks into a single universal system, reducing complexity while maintaining comprehensive information.
2Productivity
If manual quality assessment methods are used for perishable products, then quality control can be performed, but the process is time-consuming and labor-intensive
Solution Approach 1:
The system automatically generates quality codes by processing temperature data and applying assessment algorithms without requiring manual intervention. This self-service approach resolves the contradiction by enabling rapid quality assessment that improves productivity while minimizing the time loss associated with manual evaluation methods.
Solution Approach 2:
The patent replaces manual quality assessment mechanisms with an automated computational system that processes temperature data and generates quality codes algorithmically. This substitution resolves the contradiction by eliminating time-consuming manual processes while maintaining or improving assessment accuracy and efficiency.
3Measurement precision
If temperature monitoring is performed without product-specific parameters, then general temperature data can be collected, but the monitoring lacks accuracy for different perishable product types
Solution Approach 1:
The system applies different quality assessment criteria and temperature thresholds tailored to specific product types (e.g., different parameters for fruits, vegetables, meats). This local quality approach resolves the contradiction by providing high measurement precision for each product category while maintaining adaptability across diverse perishable goods through customized assessment protocols.
Solution Approach 2:
The patent modifies monitoring parameters based on product-specific characteristics, adjusting temperature ranges, assessment weights, and quality thresholds to match the sensitivity requirements of different perishable products. This parameter adaptation resolves the contradiction by achieving precise measurements for each product type while preserving versatility across the full range of perishable goods.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A system and method for assessing a supply chain for a perishable product. In various embodiments, the present invention provides a quality code for a perishable product which encodes a plurality of the most important performance metrics of the cold chain for the perishable product, including food quality oriented measures such as cut-to-cool time, transportation quality and accumulated shelf-life loss, and food safety oriented measures such as most probable number range for microorganism growth into a compact, modular and simple to read format.