Read-After-Print Label Verification for Robotic Handling
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Solution Overview
Problem
Existing printer verification methods fail to accurately assess the accuracy and quality of multiple variable labels printed on substrates, leading to potential misinterpretation and errors in robotic handling and automation processes, particularly in commercial and industrial applications where label orientation, density, and readability are critical.
Innovation Solution
A read-after-print correlation and control system using a controller interfaced with an image sensing module and photo sensors to evaluate the printed labels against pre-defined standards, ensuring accurate alignment, orientation, and quality by comparing printed pixels with commanded pixels, and determining criticality through a weighing system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple variable labels are printed on a substrate for robotic handling, then productivity is improved, but measurement precision deteriorates due to difficulty in accurately assessing label accuracy and quality
Solution Approach 1:
The system performs preliminary capture of the printed label image immediately after printing, before the label is removed from the substrate. This allows verification of print accuracy, orientation, and quality to be completed in advance, enabling identification of defective labels before they enter the robotic handling process.
Solution Approach 2:
The system creates a digital copy of the printed label through image capture and processing. This digital representation is then analyzed against verification criteria to assess label quality, orientation, and accuracy without physically manipulating the actual label, enabling precise measurement of multiple labels efficiently.
2Adaptability or versatility
If label orientation and positioning are varied for different applications, then adaptability is improved, but manufacturing precision deteriorates due to challenges in maintaining accurate print placement
Solution Approach 1:
The verification system dynamically adjusts verification parameters based on the specific label orientation and positioning requirements. It can handle labels in various orientations (0°, 90°, 180°, 270°) and positions by adapting the image analysis criteria accordingly, allowing flexible label deployment while maintaining precision verification for each configuration.
Solution Approach 2:
The system adds the dimension of image processing and coordinate transformation to the verification process. By capturing images and transforming coordinates based on detected label orientation, the system can accurately verify print placement precision regardless of the label's rotational or positional state on the substrate.
3Reliability
If automated verification is implemented to ensure label accuracy, then reliability is improved, but device complexity increases
Solution Approach 1:
The verification system is designed to handle multiple label types, orientations, and verification criteria through a single integrated platform. It can verify bar codes, text, and graphics; accommodate different label sizes and positions; and apply various verification standards, reducing the need for multiple specialized devices while maintaining high reliability.
Solution Approach 2:
The system performs self-verification by automatically capturing images, processing them through image analysis algorithms, comparing results against verification criteria, and identifying defective labels without human intervention. This automated self-service approach ensures consistent reliable verification while keeping the operational interface simple.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances machine automation by ensuring compliance with standards, preventing misinterpretation, and enabling the qualification of labels for subsequent processes by accurately assessing label quality and criticality, thus reducing errors and improving process reliability.
Implementation Method 1
an array of light emitting diodes (LED's) for providing a light source and a array of photo sensors interfaced with a lens for obtaining a reflective output
Data Source
AI summary
A printer and a process for correlating printed subject matter with subject matter that is meant to be printed by a printer with a printing mechanism or print engine such as a thermal printer including a print head, a platen, a media upon which labels are printed and a printer controller for imparting print data to the print head. An imager sends printed data as imaged to a read after print (RAP) controller for comparing the data received from the imager to data imparted to the print head or other printing mechanism. A tap, taps the data imparted from the print head and correlates it with the imaged data to determine the media speed, the image alignment, label analysis, weighing of blemishes, the gaps printed on a label, and other criteria.