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.
Use Cases
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
Concentio Serves
Logistics and
packaging industry
Construction and
manufacturing industries
Industrial plant
& equipment firms
Concentio®
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
Concentio has been built using
the following technologies
Bayesian networks
Reinforcement learning
Generic rule-based machine learning
Heuristic algorithms
Data mining
Big data integration
Big data analytics
Reverse engineering
Key Differentiators &
Business Benefits
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Ready to Use UI
Pre-built graphical user interface (GUI) & APIs for quick deployment & integration with clients’ existing workflow.
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Customizable Alerts
Customizable graphs and alerts based on prescriptive analysis as per client requirements.
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Fingerprint
Generates an IoT network fingerprint based on time-series data to predict anomalies in the incoming data.
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