Part Traceability Using Vision-Based Digital Trace Records
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Solution Overview
Problem
Current tracking and traceability methods in manufacturing industries are inefficient and labor-intensive, relying on manual processes and physical tags, which slow down production and increase costs, while being mandatory in many sectors.
Innovation Solution
Implementing a digital-based approach that integrates imaging sensor devices and machine-vision technology to generate digital trace records, aggregating temporal and spatial information with artificial reasoning, eliminating the need for physical tags and barcodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual sorting and labeling methods are used for tracking and traceability, then implementation is simple and familiar, but production efficiency decreases and labor costs increase
Solution Approach 1:
The patent replaces manual mechanical sorting and labeling operations with an automated vision-based identification system. Imaging sensors capture images of parts, and image processing algorithms automatically identify and track components without human intervention, thereby eliminating the need for manual labor while maintaining simple implementation through software-based solutions.
Solution Approach 2:
The patent creates digital copies of physical parts through image capture and processing. Instead of physically tagging parts with barcodes or RFID labels, the system generates digital representations (images) of the parts themselves, which are then processed and stored in a database to enable tracking and traceability throughout the manufacturing process.
2Loss of time
If physical tags and barcodes are attached to parts, then tracking information can be recorded, but production time increases and costs increase
Solution Approach 1:
The patent extracts the tracking information directly from the visual appearance and features of the parts themselves, rather than requiring separate physical tags or barcodes to be attached. The imaging system captures inherent characteristics of the parts (shapes, markings, features) and uses these for identification and tracking, eliminating the additional time and cost of attaching separate identification elements.
Solution Approach 2:
The patent creates digital copies of the physical parts through imaging, storing visual representations and extracted features in a database. These digital copies contain all necessary tracking information, eliminating the need for physical tags while preserving complete traceability data throughout the manufacturing process.
3Reliability
If laser engraving or RFID tags are used for part identification, then traceability is improved, but manufacturing complexity and costs increase
Solution Approach 1:
The patent replaces physical modification methods (laser engraving) and electronic tagging (RFID) with non-contact optical imaging and computational analysis. The system uses imaging sensors to capture part features and algorithms to extract identification information, achieving reliable traceability without altering the physical parts or adding electronic components, thereby maintaining manufacturing simplicity.
Solution Approach 2:
The patent creates comprehensive digital copies of parts through high-resolution imaging, capturing all visual features and characteristics. These digital representations serve as reliable identifiers and are stored in a database, providing traceability equivalent to or better than physical tagging methods while avoiding the complexity and cost of laser engraving or RFID implementation.
Data Source
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AI summary
Systems, techniques, and computer-program products are provided for tracking and traceability of parts of a finished product. In some embodiments, the tracking and traceability generates streams of semantic data obtained from an imaging sensor system that records the execution of a manufacturing process in industrial equipment. The execution of the manufacturing process yields a finished product from initial materials and/or parts. The tracking and traceability also implements artificial reasoning about the execution of the manufacturing process to generate assertions that characterize the execution of the manufacturing process. Semantic data and assertions can be aggregated into a digital trace record that tracks a defined component of the finished product throughout the execution of the manufacturing process and permit tracing the component to a defined event within the manufacturing process.