Time-Based Fingerprinting for Production Line Item Traceability
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Solution Overview
Problem
Existing methods for tracing workpieces in production lines, such as those in the lumber or food processing industries, often require costly hardware investments and adaptations, especially when physical tags cannot be attached, limiting effective traceability and data linkage across production steps.
Innovation Solution
A method that utilizes time differences between measurements from multiple devices to create a unique pattern or 'fingerprint' for each item, allowing for the correlation and linkage of time stamps and associated item parameters without additional hardware, using existing measuring devices and data storage systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If physical tags (RFID, bar codes, QR-codes) are attached to workpieces for traceability, then item identification and data linkage are improved, but device complexity and manufacturing cost increase
Solution Approach 1:
The invention extracts the identification function from physical tags and transfers it to the workpiece itself by utilizing its naturally occurring unique characteristics (grain patterns, knots, color variations). This eliminates the need for separate tagging hardware while maintaining traceability through video recognition of the workpiece's inherent features.
Solution Approach 2:
The video recognition system serves multiple functions: it identifies the workpiece, creates a unique fingerprint pattern, tracks the workpiece through production stages, and links measurement data to specific workpieces. This multi-functional approach replaces multiple separate systems (tagging, reading, tracking) with a single integrated solution.
2Reliability
If scanners and production line adaptations are mounted for identification, then item tracking capability is improved, but manufacturing cost and device complexity increase
Solution Approach 1:
The workpiece serves itself for identification by utilizing its own naturally occurring characteristics (grain patterns, knots, color variations) as the identification marker. The existing video infrastructure captures these features without requiring additional scanning hardware or production line modifications, making the system self-sufficient and cost-effective.
Solution Approach 2:
Instead of physically tagging the workpiece, the system creates a digital copy or representation of the workpiece's unique visual characteristics (fingerprint pattern). This digital fingerprint is then used for identification and tracking, eliminating the need for physical tags and associated hardware infrastructure.
3Device complexity
If time-based fingerprinting is used instead of physical tags, then device complexity is reduced, but measurement precision requirements increase
Solution Approach 1:
The identification process is segmented into distinct stages: capturing video frames at multiple production stages, extracting unique visual features from each frame, creating time-stamped fingerprint patterns, and matching these patterns across different time points. This segmentation allows each stage to be optimized independently, reducing overall system complexity while maintaining precision through cumulative evidence.
Solution Approach 2:
The system performs preliminary capture and analysis of the workpiece's visual characteristics at the beginning of the production process, creating a reference fingerprint pattern before the workpiece undergoes transformations. This preliminary action establishes a baseline for later comparison, reducing the precision burden on subsequent measurement stages.
Data Source
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AI summary
The present invention relates to and a system for linking item parameters of items processed in a production line comprising a plurality of measuring devices configured to measure item parameters. The method comprises retrieving a time series of time stamps for each measuring device indicative of when an item passed the respective measuring device. Each time stamp is associated with a measured item parameter value. A set of time differences are determined between consecutive time stamps for each of the time series of time stamps. Each time difference is associated with a time stamp. Correlating subsets of time differences associated with at least two measuring devices. When the subsets of time differences match, associating the corresponding time stamps from the matching subsets of time differences with each other. The associated time stamps are stored in a data storage device.