Maximizing Asset Lifecycles with Predictive Maintenance Powered by Industrial AI
For publicly owned utilities (POUs) in North America, the health and longevity of critical infrastructure is central to delivering reliable and affordable service to communities. Yet, many utilities are grappling with aging assets, constrained budgets, and rising expectations for transparency, sustainability, and resilience. Reactive maintenance and periodic upgrades no longer suffice. Instead, utility leaders are turning to predictive maintenance powered by Industrial AI to extend asset lifecycles, reduce costs, and future-proof their operations.
The Asset Challenge for Public Utilities
- Aging Infrastructure: Many assets are 50-70 years old, with replacement costs far outpacing available capital.
- Limited Funding: Every dollar spent must be justified to boards, councils, and the public, making asset management a balancing act between risk, reliability, and affordability.
- Manual, Disconnected Systems: Siloed data and legacy processes make it difficult to track asset health, schedule maintenance, and report on performance.
- Regulatory and Sustainability Mandates: Utilities must meet stringent compliance standards and demonstrate progress on ESG goals.
- Climate Resilience: Extreme weather events and shifting demand patterns require assets to be more resilient than ever.
These realities demand a smarter, more proactive approach to asset management.
Predictive Maintenance: The Industrial AI Advantage
Industrial AI is transforming asset management for utilities by enabling predictive, data-driven maintenance strategies that deliver measurable results:
1. From Reactive to Predictive
Traditional maintenance relies on fixed schedules and manufacturer recommendations. Predictive maintenance, powered by AI, leverages real-time data from IoT sensors, SCADA systems, and enterprise platforms to:
- Anticipate Failures: AI algorithms analyze asset health, usage patterns, and environmental factors to forecast potential breakdowns before they occur.
- Optimize Interventions: Maintenance is scheduled based on actual asset condition, not arbitrary timelines, reducing unnecessary work and minimizing downtime.
- Extend Asset Lifecycles: Studies show predictive and condition-based maintenance can extend equipment life by up to 80%, buying valuable time for utilities to plan upgrades.
2. Automating Maintenance Workflows
Public utilities often lack the resources for manual oversight of every asset. Industrial AI automates key workflows:
- Service Requests: When AI detects a maintenance issue, it automatically initiates a work order, checks inventory for required parts, and schedules the right crew.
- Procurement Integration: Advanced systems can even generate purchase orders for approval, ensuring timely acquisition of critical components.
- Mobile Access: Field crews receive real-time updates and instructions, improving first-time fix rates and safety.
3. Managing Critical Outages and Resilience
While every utility strives to eliminate outages, some are unavoidable. Predictive maintenance powered by AI enables:
- Outage Forecasting: AI delivers advanced insights into expected failures, allowing utilities to plan and communicate outages proactively.
- Digital Twin Simulation: Utilities can simulate outage scenarios, forecast impacts, and select the lowest-risk execution plan, minimizing disruption and risk.
- Multi-Threaded Decision-Making: AI draws from all areas of the operation people, parts, schedules, to optimize response and recovery.
4. Transparency, Compliance, and Community Trust
Public utilities are accountable to their communities and regulators. Industrial AI supports:
- Audit-Ready Reporting: Automated logs and compliance documentation simplify regulatory reporting and build public trust.
- ESG Integration: Sustainability metrics are embedded into asset management, supporting decarbonization and circular operations.
- Real-Time Dashboards: Leadership and the public can track asset health, maintenance activities, and performance metrics.
Real-World Impact: Doing More for Communities
The benefits of predictive maintenance powered by Industrial AI are clear:
- Cost Savings: Utilities report up to 25% reduction in maintenance costs and 70% reduction in outages.
- Asset Longevity: Asset lifespans can increase by 14–17%, deferring costly replacements and maximizing public value.
- Operational Efficiency: Automated workflows and mobile tools free up staff for higher-value tasks, improving productivity and morale.
- Sustainability: Optimized maintenance reduces energy consumption, emissions, and waste, supporting ESG goals.
- Resilience: Utilities are better prepared for extreme weather and other disruptions, ensuring reliable service for their communities.
Customer Success: Leading by Example
Utilities like Elvia (Norway’s largest power distributor) and Portsmouth Water have embraced predictive maintenance with IFS and Copperleaf:
- Elvia uses IFS Cloud on Microsoft Azure to make data-driven decisions, continuously managing assets for maximum performance and uptime.
- Portsmouth Water replaced manual processes with integrated asset management and investment planning, gaining efficiency, visibility, and control over maintenance and capital projects.
These organizations are not just maintaining assets, they’re building resilient, future-ready infrastructure that delivers lasting value to their communities.
Conclusion:
For executives in public utilities, predictive maintenance powered by Industrial AI is more than a technology upgrade, it’s a strategic imperative. By embracing AI-driven asset management, utilities can:
- Extend the life of critical infrastructure and defer costly replacements.
- Reduce maintenance costs and minimize outages.
- Build transparency, trust, and long-term value for the public they serve.
Now is the time to lead the transformation. With Industrial AI, public utilities can maximize asset lifecycles, future-proof their operations, and deliver on their promise of reliable, affordable service for generations to come.
SOURCE: John Di Stasio (2025 December 19) Maximizing Asset Lifecycles with Predictive Maintenance Powered by Industrial AI. IFS Blog. https://blog.ifs.com/maximizing-asset-lifecycles-with-predictive-maintenance-powered-by-industrial-ai/
