Smart Vision System for Continuous Material Defect Detection
Scalable Inspection Solution for Fishing Nets, Textiles, and More
Introduction
Continuous materials such as fishing nets, textiles, conveyor belt products, and industrial fabrics require precise, real-time defect detection to ensure quality and reduce waste.
Our Smart Vision System combines industrial cameras, advanced optics, and AI-powered analysis to detect defects in real time — even at production speed.
This solution is scalable, meaning a single network and workstation can support up to 10 inspection stations, lowering costs as you expand.
Key Features
- Two Camera Options:
- Line Scan Camera – ultra-high resolution for high-speed, continuous inspection
- Area Scan Camera – cost-effective for moderate-speed applications
- AI Machine Learning – detects holes, tears, and pattern irregularities
- Industrial-Grade Components – built for 24/7 operation in harsh environments
- Scalable Architecture – shared network, workstation, and software for multiple stations
- Web-Based Interface – operators can monitor defects and generate reports from any browser
System Diagram
flowchart TB
A["Material on Conveyor"] --> B["Camera (Line Scan or Area Scan) + Computar V2518FIC-MPYIR Lens"]
B --> C["Workstation (Shared)"]
C --> D["GigE Switch (Shared)"]
D --> E["Database & AI Server"]
C --> F["Operator Dashboard"]
C --> G["Reports & Alerts"]
Technology Comparison
Feature | Line Scan Camera | Area Scan Camera | Laser Profiling / 3D Sensor |
---|---|---|---|
Best For | Continuous, high-speed materials (fishing nets, textiles, films) | Medium-speed inspection, general defect detection | Surface topology inspection, 3D defect analysis |
Resolution | Extremely high (1 pixel per line × object length) | Limited by sensor megapixels | Depth + 2D resolution |
Speed | Very fast, ideal for moving objects | Slower, depends on exposure time | Moderate, limited by scanning rate |
Lighting Requirements | Needs stable, uniform illumination | Needs good lighting but more flexible | Often uses built-in laser light |
Cost | Higher camera cost, encoder required | Lower camera cost, no encoder needed | Higher sensor cost than area scan |
Software Complexity | Moderate (line-by-line image assembly) | Lower | Higher (3D point cloud processing) |
Scalability | Excellent for multiple stations | Excellent | Good but higher per-unit cost |
Example Use Cases | Fishing nets, plastic film, paper rolls | Textile QC, sheet metal inspection | Crack depth measurement, roughness inspection |
Hardware Components
Per-Station Hardware (Camera + Lens + Mounting)
Line Scan Version
- Basler R2L4096-84G5M
- Computar V2518FIC-MPYIR Lens
- Rotary Encoder for precise trigger timing
- Mounting brackets & cabling
Area Scan Version
- Basler a2A4504-5gcIP67
- Computar V2518FIC-MPYIR Lens
- LED Lighting for uniform illumination
- Mounting brackets & cabling
Shared Network Equipment (One-time, supports up to 10 stations)
- Cisco CBS350-24P-4X GigE Switch
- Intel X550-T2 Dual-Port 10GbE NIC
- Industrial-grade Cat6a cabling
Shared Workstation (One-time, supports up to 10 stations)
- Lenovo ThinkStation (i5-14400, 32GB DDR5, RTX 4000 Ada, 1TB SSD, RAID HDD)
- High-performance GPU for real-time AI processing
Software
Our software is built with Django + DRF for robust backend processing and a responsive web dashboard for operators.
Core Features:
- Real-time defect detection with AI models
- Historical data storage and trend analysis
- Multi-station monitoring from one interface
- Automated alerts and defect reports
- Role-based access control for operators, managers, and engineers
Scalability Advantage
Unlike single-purpose vision systems, this design allows adding more inspection stations without major additional costs.
Shared infrastructure (network, workstation, and software) means the cost per station drops significantly as you scale.
Example Costs (THB)
1 Station – Line Scan: 1,003,062 THB
5 Stations – Line Scan: 1,325,914 THB (265,183 THB per station)
1 Station – Area Scan: 992,062 THB
5 Stations – Area Scan: 1,275,914 THB (255,183 THB per station)
Conclusion
Whether you’re inspecting fishing nets, textiles, or any continuous product, our Smart Vision System delivers accuracy, speed, and scalability.
By combining industrial cameras, advanced optics, and AI defect detection, manufacturers can reduce waste, improve quality, and scale cost-effectively.
📩 Contact us today to schedule a demo or discuss your specific inspection needs.
Get in Touch with us
Related Posts
- Building a Real-Time Defect Detector with Line-Scan + ML (Reusable Playbook)
- How to Read Source Code: Frappe Framework Sample
- Interface-Oriented Design: The Foundation of Clean Architecture
- Understanding Anti-Drone Systems: Architecture, Hardware, and Software
- RTOS vs Linux in Drone Systems: Modern Design, Security, and Rust for Next-Gen Drones
- Why Does Spring Use So Many Annotations? Java vs. Python Web Development Explained
- From Django to Spring Boot: A Practical, Visual Guide for Web Developers
- How to Build Large, Maintainable Python Systems with Clean Architecture: Concepts & Real-World Examples
- Why Test-Driven Development Makes Better Business Sense
- Continuous Delivery for Django on DigitalOcean with GitHub Actions & Docker
- Build a Local Product Recommendation System with LangChain, Ollama, and Open-Source Embeddings
- 2025 Guide: Comparing the Top Mobile App Frameworks (Flutter, React Native, Expo, Ionic, and More)
- Understanding `np.meshgrid()` in NumPy: Why It’s Needed and What Happens When You Swap It
- How to Use PyMeasure for Automated Instrument Control and Lab Experiments
- Supercharge Your Chatbot: Custom API Integration Services for Your Business
- How to Guess an Equation Without Math: Exploring Cat vs. Bird Populations
- How to Build an AI-Resistant Project: Ideas That Thrive on Human Interaction
- Build Your Own Cybersecurity Lab with GNS3 + Wazuh + Docker: Train, Detect, and Defend in One Platform
- How to Simulate and Train with Network Devices Using GNS3
- What Is an LMS? And Why You Should Pay Attention to Frappe LMS