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


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

  • Ready to Use UI

    Pre-built graphical user interface (GUI) & APIs for quick deployment & integration with clients’ existing workflow.

  • Customizable Alerts

    Customizable graphs and alerts based on prescriptive analysis as per client requirements.

  • Fingerprint

    Generates an IoT network fingerprint based on time-series data to predict anomalies in the incoming data.