Print Control Element Identification via Machine-Readable Codes
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Solution Overview
Problem
Current methods for remote print quality control in smaller printing presses require specialist knowledge and are inefficient, as they rely on manual data entry and image classification, which is time-consuming and prone to errors, especially when using mobile devices like cameras and hand densitometers.
Innovation Solution
A method utilizing machine-readable codes such as QR codes or barcodes, combined with OCR processing, allows for automatic data collection and wireless transmission of image data to a support center, enabling users without printing expertise to perform remote quality analysis using mobile devices with pre-analysis capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual data entry and image classification are used for remote quality control, then users can perform quality checks without specialized equipment, but the process becomes time-consuming and requires specialist knowledge
Solution Approach 1:
Machine-readable codes are printed on the control elements beforehand, containing all necessary identification and classification information. This preliminary encoding eliminates the need for manual data entry and image classification during quality control, as the system automatically reads and processes the pre-prepared code information.
Solution Approach 2:
The control elements themselves carry their own identification information through machine-readable codes. When captured by a camera, these codes automatically provide the system with all necessary metadata about the control element type, position, and parameters, making the system self-describing and eliminating dependency on specialist knowledge for data entry.
2Productivity
If manual examination of control elements is performed, then quality control can be conducted with simple equipment, but accuracy and efficiency decrease due to human error and time constraints
Solution Approach 1:
The manual mechanical process of examining control elements is replaced by an automated optical system. A camera captures images of the machine-readable codes on control elements, and software automatically reads, classifies, and evaluates the quality data, eliminating human error and time constraints while improving both productivity and measurement precision.
Solution Approach 2:
Machine-readable codes serve as an intermediary between the physical control elements and the digital evaluation system. These codes encode all necessary information about the control elements, enabling automatic identification, classification, and quality assessment without requiring manual intervention or specialist interpretation.
3Loss of information
If comprehensive quality data is collected manually, then detailed analysis is possible, but the complexity of data management and transmission increases
Solution Approach 1:
Quality data is segmented and encoded into structured machine-readable codes on individual control elements. Each code contains specific information about that element's position, type, and measured parameters. This segmentation allows for systematic automated collection, management, and transmission of comprehensive data without increasing system complexity, as the data is already organized in a machine-processable format.
Data Source
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AI summary
A method for identifying print control elements for quality data acquisition, comprising the following steps: • Encoding positional information into a human-readable identification code • Encoding specific print job information and the human-readable identification code into a machine-readable data code • Positioning the machine-readable data code and the identification code next to their associated print control element on the printing substrate • Photographing the printed print control element and the adjacent machine-readable data code using the information from the adjacent identification code and processing the data with a mobile communication device equipped with a camera and a communication interface • Exporting the generated image data to a support computer via the communication interface of the mobile communication device • Decoding the machine-readable data codes • Analyzing the image data on theSupport computer using the information obtained from the decoded machine-readable data code • Transmission of the analysis results from the support computer to the mobile communication device • Correction of the incorrect settings found in the printing press producing the printed products based on the image analysis