Concentio Predictive Maintenance

Predictive Maintenance, an Enterprise AI application of Concentio by Scry Ai is built with the core tenet of maintaining comprehensive asset risk assessment and maintenance.

Predictive Maintenance, a Scry Ai Concentio production aggregates data across IoT and non-IoT data sources with machine learning and computer vision along with external data. The core Predictive Maintenance application feature stands in its ability to analyze and extract more than 200 relevant data attributes in order to provide descriptive analytics in asset risk management.

Key Features

  • 30+ Proprietary AI and ML Algorithms.
  • Automated Ontology with dynamic updates.
  • ML empowered component failure risk scores.
  • Ability to ingest, process and analyze data from images and videos using Computer Vision.
  • 90%+ Accuracy from integration onwards.
  • Human-in-the-loop” accuracy improvements through reinforced learning.

Use Cases

  • Aggregates data across IoT and non-IoT data sources with machine learning and computer vision along with external data.
  • Analyzes and extracts more than 200 data attributes to provide descriptive analytics in asset risk management.
  • Detects data integrity from a device “fingerprint” in order to alert if the incoming data does not match the quality expected from a specific device.

Concentio’s Predictive Maintenance delivers high end Competitive Advantages such as:

  • Equipment Data Anomaly Detection via Fingerprinting
    • Generates time-series data based unique equipment fingerprint.
    • Incorporates the specifications provided by various equipment manufacturers.
    • Alerts the user if the incoming data does not conform to the fingerprint of this equipment and its components.
  • Failure Forecasting
    • Provides visualization of risks across asset portfolios and businesses.
    • Provides trade-offs between time and cost for fixing an equipment.
    • Tracks, benchmarks, and ranks performance of individual pieces of equipments based on probability and impact of failure.
  • Time and Cost Reduction
    • Reduced capital expenditures by driving asset replacement decisions.
    • Reduced inventory costs by anticipating the need for potential replacement.
  • Ready to Use Integration
    • Ready to use data ingestion connectors and APIs.
    • Pre-built connectors to online platforms and sources for enhancing anomaly detection with external data.

Scry Ai’s Concentio is currently serving Predictive Maintenance solutions in industries of:

  • Logistics & Packaging
  • Construction
  • Industrial Plant & Equipment
  • Telecom
  • Healthcare
  • Agriculture
  • Mining

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