Food Processing Traceability for Product-Level Impact Tracking
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Solution Overview
Problem
Existing food production systems lack granular information about specific food processing units and settings, which hinders the determination of environmental impact and resource efficiency, limiting the ability to optimize production and reduce environmental footprint.
Innovation Solution
A computer-implemented method and system that tracks process traceability and event data from food processing units, determines settings used during production, and calculates an environmental impact measure by combining utility consumption data, including locally produced electricity and weather forecasts, to provide detailed environmental information linked to individual food product packages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If detailed process traceability data and event data are collected and combined to determine settings for each food product, then measurement precision and information completeness are improved, but device complexity and data processing requirements increase
Solution Approach 1:
The patent segments the food production process into discrete processing units and time slots, with each unit having its own process traceability data and event data. This segmentation allows granular tracking of settings for each product batch while organizing data in manageable segments that can be processed independently, reducing overall system complexity.
Solution Approach 2:
The patent introduces a data processing apparatus that acts as an intermediary between the food processing units and the environmental impact assessment. This intermediary consolidates and processes the complex data from multiple sources, transforming raw process traceability and event data into meaningful settings information without requiring direct complex interactions between all system components.
2Quantity of substance
If utility consumption data is distributed and allocated to individual food products based on processing settings, then resource efficiency measurement is improved, but calculation complexity increases
Solution Approach 1:
The patent applies local quality by allocating utility consumption to specific food products based on their local processing conditions and settings. Each product receives a customized allocation of water, energy, and other utilities based on the actual settings used during its specific processing journey through different units, enabling precise resource accounting without requiring complex system-wide calculations.
Solution Approach 2:
The system performs preliminary actions by pre-calculating and storing the relationship between processing settings and utility consumption for different processing units. This allows the data processing apparatus to quickly allocate resources to individual products by referencing pre-established consumption patterns rather than performing complex real-time calculations for each product.
3Loss of information
If environmental impact measures are calculated for individual food products with detailed traceability, then information completeness is improved, but processing time increases
Solution Approach 1:
The patent implements preliminary action by pre-establishing the framework for environmental impact calculation, including pre-defining the relationship between processing settings, utility consumption, and environmental impact factors. This allows the system to quickly generate environmental impact measures for individual products by applying pre-configured calculation rules to the collected process data, rather than performing comprehensive environmental assessments from scratch for each product.
Solution Approach 2:
The system utilizes parameter changes by transforming detailed process traceability data and utility consumption data into standardized environmental impact parameters. This transformation consolidates multiple data dimensions into key environmental metrics that can be processed efficiently while retaining the essential information needed for environmental assessment.
4Productivity
If food production is monitored with granular detail to enable environmental optimization, then productivity is improved, but ease of operation decreases
Solution Approach 1:
The patent implements self-service by enabling the food production system to automatically monitor, track, and optimize its own resource consumption and environmental impact. The data processing apparatus autonomously consolidates data from multiple processing units, allocates utility consumption, and calculates environmental measures without requiring manual intervention, allowing the system to improve productivity while maintaining operational simplicity.
Solution Approach 2:
The system applies feedback by using the calculated environmental impact measures and resource efficiency data to automatically adjust and optimize future production processes. This closed-loop feedback mechanism enables continuous improvement of resource efficiency while the automated nature of the feedback process maintains ease of operation by eliminating manual analysis and adjustment requirements.
Data Source
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AI summary
A computer-implemented method (500) for monitoring a food processing system (100), arranged to produce a food product (102), using a data processing apparatus (112) is provided. The method comprises receiving (502) process traceability data (200) related to the food product (102), wherein the process traceability data (200) comprises information about which food processing units (104a-e) that were involved in processing the food product (102) as well as during which time slots the food processing units were involved for processing the food product (102), receiving (504) process event data (202) related to the food processing units of the food production system (100), wherein the process event data (202) comprises information about state changes of the food production units that occurred during processing of the food product (102) as well as points of time when the state changes occurred, receiving (506) settings (204) of the processing units (104a-e) associated with different states, determining (508) the settings used for the food production units (104a-e) during different time slots by combining the process event data (202) and the settings of the processing units (204) associated with the different states, and determining (510) the settings of the food production units (104a-e) used for processing the food product (102) by combining the process traceability data (200) and the settings used for the food production units during the different time slots, and providing (512) the settings of the food production units (104a-e) used for processing the food product (102).