Edge InspectiON
Fully automated defect detection and classification for the timely identification of flaws
AI-powered machine vision solutions for complex quality requirements
Customizable and flexible implementation for any decor and surface
Prevention of false detections to boost product quality and competitiveness
AI-Powered Quality Control for Furniture Panels
Put an end to defective edges and costly false detections in production!
The intelligent edge inspection system from Hecht automatically detects and classifies defects on furniture edges. Utilizing modern machine vision and AI methods, this solution adapts flexibly to any decor, reliably ensuring precise, durable edges with maximum process reliability.
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More InformationFunctions
- Automatic detection and classification of defects such as edge bands that are too short, wrinkles, dents, or contamination
- Image processing and analysis of furniture edges using AI, machine vision, and mathematical modeling techniques
- Flexible acquisition and inspection of widely varying decors, colors, and surfaces
- Continuous inline inspection and data processing directly within the production process
Application images
Software-options
- Module for customer- and decor-specific inspection profiles
- Customized interface and data integration (ERP/MES)
- Logging and dashboard for defect analysis in the production process
- Integration of AI and machine vision algorithms
- Data archiving
Advantages
Automated Defect
Detection: Instant AI detection of defects within the production process
Maximum Precision
Reliable reduction of false detections and customer complaints
Maximum Process Reliability
Secure quality control across any decor or surface
Edge InspectiON
The system identifies typical quality flaws on furniture edges, such as chipping along the edge, chatter marks, dents, edge bands that are too short or too long, top-side wrinkles, surface contamination, etc.
Through the use of flexible AI and machine vision algorithms, the inspection solution can be customized to adapt to any changing decors, colors, coatings, and materials.
Yes, the system is designed for integration directly into the edgebander. Typically, an available space of approximately 400 mm in width within the line is sufficient.
Conventional inspection systems are often prone to false detections when handling complex patterns. AI-powered image processing significantly reduces this error rate and ensures stable manufacturing processes.
Camera-based inspection offers significant advantages over purely measuring systems (such as 3D systems). Flaws that affect visual appearance without causing geometric changes can only be detected by camera systems. Furthermore, camera images are easy for operators and quality assurance personnel to understand and quickly interpret, whereas representations generated from 3D point clouds are far more complex.
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For new decors, images are captured and trained using an automated process. Only good (non-defective) parts are required for training. During production, defects are then identified as deviations from the trained target state. Typically, a sample size of around 20–30 images is sufficient.
Technical data
- Operation | Control | OS: PC control | Linux or Windows
- Panel Thickness: 5 mm – 60 mm
- Feed Speed: Up to 60 m/min
- Design: Modular setup with 1–3 cameras (top, bottom, narrow side) based on customer requirements
- Installation Width: Approx. 400 mm
- Option: Height adjustment for the top camera (if no built-in height adjustment is present
Use our service.
Phone: +49 (0)7143-8159-0
Ottmarsheimer Hoehe
Heinrich-Hertz-Str. 3-5
74354 Besigheim
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