Visual Inspection of Inkjet Coding and Laser Coding on SIG Combibloc Packaging
This is a highly specific topic in the food and beverage packaging industry—particularly for aseptic carton packaging like SIG Combibloc—and represents a critical quality inspection step. Let’s systematically break down the technical points, challenges, and solutions for the visual inspection of inkjet codes and laser codes on SIG combibloc packaging.
Core Objective
The core goal of the visual inspection system is to ensure 100% readability, accuracy, and completeness of printed information such as production dates, expiration dates, batch numbers, and QR codes, in order to meet regulatory requirements, traceability needs, and consumer trust.
Part 1: Characteristics and Inspection Differences Between the Two Coding Technologies
Feature | Inkjet Coding (CIJ/DOD) | Laser Coding |
|---|---|---|
Principle | Tiny ink droplets are ejected onto the packaging surface via a printhead. | A laser beam causes physical/chemical changes on the packaging material surface (often film or coating), creating the mark. |
Color | Typically black, blue, etc., with high contrast against the packaging background. | Usually a change in the material’s base color (e.g., light gray, brown), with lower contrast against the packaging background. |
Substrate | Widely adaptable, adheres well to various coatings. | Material-sensitive; requires specific coatings (laser-sensitive coatings) for clear marking. |
Inspection Challenges | Ink splatter, broken characters, insufficient/excessive ink, smudging, incomplete drying causing smears. | Low contrast, uneven energy leading to inconsistent depth, over-burning (piercing), under-burning (faint marking). |
Key Inspection Dimensions | Presence, completeness, clarity, position, content accuracy. | Presence, readability (core challenge), completeness, position, content accuracy. |
Part 2: Core Components of the Visual Inspection System
Image Acquisition Hardware
Inkjet Coding: Usually, white ring light or dome light provides good contrast.
Laser Coding: Targeted lighting is required. Common methods include low-angle dark-field illumination (e.g., bar light) to highlight the micro-texture created by laser ablation and enhance contrast. Sometimes, specific wavelengths (e.g., red light) are used to suppress background interference and emphasize the mark.
Industrial Camera: High resolution (ensures small character clarity), high frame rate (matches production line speed). For laser codes, a global shutter camera is essential to avoid motion blur.
Lighting: This is key to success, especially for laser codes.
Lens: Select appropriate focal length and depth of field to ensure clear imaging.
Image Processing and Software Algorithms
Classification Models: Directly classify codes as “OK” or “NG” (e.g., missing, severely blurred).
Segmentation Models: Precisely segment each character or code area, even on uneven backgrounds.
End-to-End Recognition: Directly read code content from images without complex preprocessing and segmentation, offering robustness for low-contrast or defective codes.
OCR (Optical Character Recognition): Used to recognize characters like dates and batch numbers. Requires a pre-trained font library suitable for industrial coding fonts, tolerant of some deformation or breaks.
QR Code/Barcode Reading: Decoding and verifying content correctness and linkability.
Preprocessing: Filtering, contrast enhancement, binarization (threshold selection for laser codes is critical).
Character Segmentation: Dividing the continuous code area into individual characters for recognition.
- Character Recognition:
Deep Learning (Mainstream Trend):
Part 3: Specific Inspection Items and Common Defects
Presence Inspection: Is there a code on the package? Is it completely missing?
Position Inspection: Is the code within the specified rectangular area? Is it skewed beyond tolerance?
Completeness Inspection:
Clarity/Readability Inspection:
Content Accuracy Inspection:
Missing/Broken Characters: Ink breaks, insufficient laser energy.
Excessive Ink Dots/Smudges: Ink splatter, inherent packaging dirt.Character Merging: Excessive ink, overlapping laser ablation areas.
Contrast: A key inspection item for laser codes. Measures the grayscale difference between characters and background.
Edge Sharpness: Are character edges clear or blurred?
OCR Comparison: Compares the recognized date/batch with information from the MES/upper-level system to prevent incorrect coding.
QR Code Validity: Decodes and verifies if the content complies with rules and can be linked to the enterprise traceability system for testing.
Part 4: Implementation Challenges and Suggested Solutions
Challenge | Suggested Solutions |
|---|---|
High-Speed Production Line | Use high-performance smart cameras or industrial PCs, optimize algorithm efficiency, and employ hardware triggers for precise image capture. |
Packaging Variety | The same line may produce products of different specifications and background colors. Create different inspection recipes for automatic switching. |
Low Contrast of Laser Codes | Customized lighting solutions are key. Experiment with coaxial light, low-angle light, or multi-angle combined lighting. Consider using polarizing lenses to eliminate glare interference. |
Complex Background Interference | SIG combibloc surfaces may have patterns or textures. Use deep learning models to better separate code features from complex backgrounds. |
Environmental Variations | Ensure lighting stability and regularly clean protective lenses. The system should have some adaptive capability or provide simple recalibration tools. |
Balancing False Calls and Misses | Set reasonable sensitivity parameters. Incorporate a “learning mode” to train the system with a large number of OK samples. Set uncertain cases as “suspected” for manual re-inspection. |
Integration with Production Line | Requires communication with coders, PLCs, and MES systems. Must receive coding information for comparison and output NG signals to drive rejection mechanisms. |
Summary
For inkjet coding on SIG combibloc, visual inspection technology is relatively mature, with the core focus on ensuring stable lighting and algorithmic accuracy. For laser coding, the success of visual inspection depends 70% on designing the optimal lighting solution for the specific packaging material (coating) and laser marking characteristics, while the remaining 30% relies on advanced image processing algorithms (especially deep learning) to ensure stable and reliable readability assessment.
During project implementation, it is strongly recommended to conduct on-site POC (Proof of Concept) testing using real packaging samples that include various defects, and validate the reliability and stability of the inspection solution at production line speeds.
