SPICA Brainbox Family
Advanced AI based Non Invasive inspection of materials and structures for assessment of service life and condition.
SPICA Brainbox Family
Advanced AI based Non Invasive inspection of materials and structures for assessment of service life and condition.
Intuitive, Innovative Features
Crack Detection
SPICA uses deep learning models to identify surface cracks with higher precision. This helps in enhancing predictive maintenance by enabling early detection, minimizing equipment failure and increasing product quality.
Color Mismatch Detection
SPICA used machine learning algorithms and image processing techniques to identify color shade variations against pre-defined standards. This ensures color consistency in manufacturing & improving product quality.
Profile Change Detection
Advanced algorithms compare and identify deviations in metal shapes, sizes with an accuracy of up to 50 microns. This technology helps in enhancing quality control of manufactured components.
Optical Character Recognition (OCR)
The system automates the extraction of text from labels & parts, with high accuracy. This streamlines inventory management & quality control.
Part Presence/ Absence
Using advanced computer vision algorithms the system can verify whether components are correctly installed or missing in assembly.
Real-Time Alerts and Notifications
The system can be easily integrated with existing conveyer lines and also be used during periodic inspections, providing real-time alerts and notifications without affecting production speed.
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