Offerings
Use a health index framework for asset maintenance
Overview
An AI-driven asset health indexing model provides electric, gas and water utility enterprises with a risk-weighted pathway to optimize transmission and distribution (T&D) infrastructure management.
Infosys Utilities leverages artificial intelligence (AI), machine learning (ML), digital twins, and edge analytics to transform operations data into actionable intelligence for predictive asset maintenance. Our solutions combine data from IoT sensors, field devices, asset logs, and enterprise systems to analyze asset issues, grid constraints and resource availability. Based on accurate analysis, the solutions recommend maintenance schedules.
Our domain experts develop Asset Health Indexing (AHI) algorithms that facilitate condition-based maintenance. Our AI / ML analytics engines integrate AHI scores and risk metrics to assess the current condition and estimate the lifespan of assets. It helps utility asset managers take informed decisions to ensure reliability and safety. For instance, replace end-of-life critical assets, prioritize maintenance in a service territory, or enhance monitoring of edge devices.
Infosys capabilities:
Vendor-agnostic, cloud-native technology stack manages utility-scale datasets, integrates and harmonizes heterogeneous data streams, and undertakes preprocessing to produce ML-ready datasets
Geospatial enablement of asset master data in ERP systems ensures data quality, integrity and spatial accuracy
AI / ML systems detect anomalies in electrical, thermal, mechanical, and chemical signal patterns, and predict performance as well as safety issues before triggering alarms mapped to thresholds, across asset types and classes
Our purpose-built machine learning models turn real-time operations and historical failure data into predictive insights that reduce downtime, improve reliability, and extend asset life.
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Drive Proactive Asset Maintenance with AI-Powered Insights
- AI solutions for real-time monitoring and prompt intervention boost productivity and streamline maintenance planning.
- Asset lifecycle cost analysis and risk analytics facilitate long-term planning while minimizing emergency shutdowns.
- Computer vision and image analytics detect physical degradation and structural fatigue across assets, enabling targeted maintenance.
Challenges & Solutions
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