Replacing Time-Based Maintenance with Predictive Analytics in Nuclear Operations |
Helping a US-based nuclear facility reduce unnecessary inspections, optimize sensor placement, and move to a smarter predictive maintenance strategy using MADE.
O&M Savings
Inspections
Potential
Strategy
Cutting Nuclear O&M Costs Without Compromising Safety or Reliability
A US-based nuclear utility was facing high operations and maintenance costs driven by frequent visual inspections and time-based preventive maintenance. Parts were often being replaced well before failure, increasing labour demand, driving up parts consumption, and reducing available operating capacity.
While this conservative approach supported compliance and safety, it also created avoidable cost and efficiency penalties. The utility wanted to shift to a more intelligent maintenance strategy that could identify emerging failures earlier, reduce unnecessary intervention, and maintain the reliability and safety standards the sector demands.
The challenge was not simply to add more monitoring. It was to determine the right sensor strategy, pair it with the right analytics, and create a real-time diagnostic approach that would support faster, better-informed maintenance decisions.
Model-Based Predictive Maintenance Design Using MADE
Integral Analytics used MADE to carry out a detailed FMEA, identifying the most common degradation mechanisms associated with each critical failure mode. This created a structured foundation for smarter maintenance decision-making.
Sensors and analytic methods were matched to the failure mechanisms that mattered most, with the goal of minimising the time between the onset of incipient failure and reliable detection.
The FMEA was translated into an automated diagnostic model that could alert analysts or subject matter experts when failure conditions were detected in real time.
Alert thresholds and communication protocols were established based on failure severity, enabling the utility to move from fixed maintenance schedules to a more targeted, predictive maintenance strategy.
“MADE enabled a shift from time-based maintenance to predictive action connecting failure behaviour, sensor strategy, and operational savings in one defensible model.”
Measurable Results. Lower Cost. Smarter Maintenance.
Estimated O&M Cost Reduction
The elimination of unnecessary inspections and wearable replacement parts produced an estimated $4.2 MM in savings over the life of the plant.
Improved Resource Allocation
Maintenance teams could focus on the assets that genuinely required attention, improving efficiency and reducing unnecessary effort.
Predictive Maintenance Foundation
The utility gained a real-time diagnostic framework to support condition monitoring, earlier fault insight, and a more sustainable maintenance strategy.
Digital Risk Twin Analysis Outputs
See What MADE Can Do for Your Predictive Maintenance Strategy
Talk to a PHM Technology RAMS specialist and discover how MADE can help you optimise maintenance strategy, improve fault visibility, and reduce lifecycle cost in complex, high-consequence environments.
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