Inline Data Matrix Grading
Data Matrix and Barcode Compliance with GS1 Standards
Challenge
Unique Device Identification (UDI) in healthcare and medical industries are typically encoded into Data Matrix barcodes which are printed onto surfaces using inkjet or laser printers. Achieving the required print quality can be difficult due to variations in printer performance, ink quality, and environmental factors like temperature and humidity. These issues can lead to an increased production line stops, product recall, and costly compliance penalties.
Meeting GS1 standards for UDI codes enables seamless interoperability between different stakeholders in healthcare, including manufacturers, distributors, and healthcare providers. This standardized approach improves inventory management, facilitates recalls, and enhances patient safety by ensuring accurate identification and traceability of medical products.
Types of data matrix defects graded by Ceyeborg‘s Inline data matrix grading solution
print loss
print growth
modulation
grid non uniform
fixed pattern damage
axial non uniform
Traditional inline vision systems that monitor barcode quality often fail to provide real-time corrective actions, resulting in delays and inefficiencies. They also fail to grade bar codes which are unreadable – making it harder for line operators to identify the type of defect and the reason it occurred. These systems typically only flag barcodes that do not meet the minimum quality standards, without offering immediate solutions to correct the issues. Other challenges include:
- Calibration inconsistencies, making it difficult to ensure that the vision systems maintain accurate and reliable quality checks.
- Difficulty in detecting subtle defects such as contrast modulation, fixed pattern damage, and grid non-uniformity, which can affect the readability and compliance of the barcodes.
- Managing the quality of barcodes on different types of surfaces and materials, which may affect the printing and scanning processes.
Solution
Ceyeborg addressed these challenges by developing a custom solution housed in a compact box containing an advanced camera system and integrated processing logic. This system directly communicates with the factory’s printing devices over a Programmable Logic Controller (PLC). The camera system continuously monitors the printed barcodes, immediately raising alarms when the quality of the codes is insufficient or fails to meet GS1 standards. This proactive system allows for real-time adjustments to the printing process, ensuring that errors are corrected promptly rather than simply flagged post-production.
Ceyeborg Inline Data Matrix Grading Cube
Ceyeborg’s solution also goes a step beyond its competitors by minimally reconstructing barcodes which are damaged beyond readability – to still provide a score to the different GS1 standard grading criteria. This allows for better error identification when codes fail beyond readability. Using AI algorithms trained on a mix of synthetically damaged barcodes and real-world examples, the minimal reconstruction of the barcode can be applied to your factory line without exhaustive data collection campaigns.
AI-based reconstruction of defected codes
The inspection stations can be connected to robust databases, enabling efficient data storage and retrieval for traceability and compliance verification. Furthermore, they are equipped to communicate over OPC UA (Open Platform Communications Unified Architecture), allowing seamless integration with your factory’s existing infrastructure and printing devices. This proactive approach not only enhances efficiency in production but also contributes to the overall integrity and effectiveness of medical device identification and traceability systems.
Ceyeborg’s automated, inline grading systems assess the readability and accuracy of UDI codes during manufacturing, helping to identify and correct issues in real-time. By detecting and grading UDI codes as they are printed, manufacturers can minimize errors, reduce the risk of product recalls, and ensure compliance with regulatory requirements.
Result
The implementation of Ceyeborg’s solution significantly improves production line effectiveness. By providing a more reactive approach compared to existing systems, the inline camera system enables immediate corrective actions, reducing machine stops and rejects.
This results in smoother, more efficient production runs and ensures that all printed barcodes meet the stringent GS1 standards.
Ceyeborg’s solution differentiates itself in the following key aspects:
- The ability to integrate the solution to the factory’s PLC using OPC UA enables dynamic adjustment of the printing process in real-time.
- Direct logging of all metrics during production into a robust database solution over your PLC.
- The ability to go beyond the capabilities of common inline barcode readers by using AI-based bar code minimal reconstruction, allowing operators to identify the source of the issue even for barcodes which are unreadable and cannot be graded by standard data-matrix grading systems.