Neural Vision develops machine learning-based quality control systems for the flexible packaging industry, specifically targeting unprinted areas during the slitting stage of flexographic production. Their technology utilizes real-time data from cameras and sensors to enhance production quality, reduce waste, and improve customer satisfaction.
Funding
$250K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
In flexible packaging production, undetected unprinted areas during the slitting stage can lead to defective products, increased waste, and reduced customer satisfaction. Traditional quality control methods often lack the speed and precision needed to identify these defects in real-time.
Solution
Neural Vision offers an automated quality control system that uses machine learning to detect unprinted areas during the slitting stage of flexographic printing. The system, called Axon, employs cameras and sensors to capture real-time data from the production line. This data is then analyzed using machine learning algorithms to identify defects and prevent them from being included in the finished product. By providing autonomous identification of production cycles, the system enables printing houses to improve quality control, reduce waste, and enhance customer satisfaction.
Target Audience
The primary customers are flexographic printing houses that produce flexible packaging materials.
Features
- Real-time detection of unprinted areas using machine learning-based vision system
- Autonomous identification of production cycles based on telemetry from cameras and sensors
- Constantly evolving data set obtained during the production cycle to improve accuracy
- Statistical data analysis for MIS systems to predict potential production problems