Production Line Fault Prediction
Automated Anomaly Detection in Production Line
Production Line Fault Prediction is an application based on proprietary machine learning and computer vision algorithms to analyze if the incoming video or data constitute an anomaly and the likelihood of failure of the corresponding product or its components.
Identifies anomalies in real time data using time series analysis and fingerprints of the production line and its components
Provides descriptive, predictive, and prescriptive insights
Alerts the user of a potentially faulty product or its components
Monitors all portions of the production line in real-time
& equipment firms
AI-based Yield Optimization application for Production Management
Production Line Fault Prediction by Scry Analytics is extremely versatile and can ingest data from several hundred components of a production line thereby alerting the user of anomalies and their potential consequences.More Detail
- 30+ proprietary AI-based algorithms, the majority using computer vision to detect anomalies
- Provides real-time validation against the software-generated fingerprints
- Time-series, and frequency domain analyses
- Real-time alerts related to anomalies
- “Human in the loop” helps the software in improving its accuracy on a continuous basis
- SCADA, DCS and various enterprise systems can be easily integrated using prebuilt APIs
- Integrated modeling supports discrete, batch, semi-batch, and continuous manufacturing processes
Concentio has been built using
the following technologies
Generic rule-based machine learning
Big data integration
Big data analytics
Key Differentiators &
Ready to Use UI
Pre-built graphical user interface (GUI) & APIs for quick deployment & integration with clients’ existing workflow.
Customizable graphs and alerts based on prescriptive analysis as per client requirements.
Generates an IoT network fingerprint based on time-series data to predict anomalies in the incoming data.