Asoba Ona Documentation

Use Case: Cummins Portfolio

Maintaining Operations Through Severe Data Loss

This use case highlights the resilience of the Ona Intelligence Layer and its ability to ensure operational continuity even in the face of significant infrastructure and data failures.

The Challenge

The Cummins portfolio, a multi-megawatt collection of assets, experienced severe sensor and telemetry failures, resulting in a 65% loss of data points. For most monitoring and analytics systems, this would be catastrophic. Missing data is typically treated as downtime, rendering analytics and performance reporting useless.

The Solution: AI-Powered Data Reconstruction

The Ona Intelligence Layer treats missing data not as an absence, but as a signal to be interpreted. Our platform immediately identified the data loss and initiated an AI-powered data reconstruction process.

  1. ARIMA-Based Interpolation: We used Autoregressive Integrated Moving Average (ARIMA) models to intelligently interpolate the missing data points based on historical patterns.
  2. Machine Learning Ensemble: The interpolated data was then fed into a machine learning ensemble to reconstruct the full operational history of the assets with high fidelity.
  3. Uninterrupted Logic: All downstream logic, from maintenance schedules to grid compliance checks, continued to function without interruption.

The Results

The Ona Intelligence Layer turned a potential operational crisis into a non-event, demonstrating the value of a true intelligence layer over a simple monitoring dashboard.