Use of Online Monitoring Data to Support Sensor Calibration Extensions - MTA-MA-032
| Administrative Items | |
|---|---|
| Date | 9/14/2026 |
| Functional Area Where Benefits Will Be Realized | Maintenance |
| Reference Implementation Guidance |
Guidelines for Instrument Calibration Extension/Reduction - Revision 2: Statistical Analysis of Instrument Calibration Data (EPRI 3002002556) US Nuclear Regulatory Commission AMS-TR-0720R2 Regulatory Guide 1.105 Rev. 4 Setpoints for Safety-Related Instrumentation |
| Industry SME | EPRI – PRR
Contact: NuclearPlantMod@epri.com |
| Previous Implementation | Please contact EPRI for implementation examples and contacts. |
| Implementation Enablers | N/A |
| Applicability | All reactor types
All geographic regions |
| Keywords | Extend calibration; calibration intervals; instrument drift; historical data; statistical analysis |
| Business Case Analysis Cross-Reference | Plant Modernization Business Case: Cost-Benefit Analysis of Calibration Interval Extensions Using OLM and Historical Calibration Methods - A Business Case Evaluation of Condition-Based Strategies in Nuclear Power Plants (EPRI 3002035082) |
Description
Traditional nuclear utility calibration programs rely on fixed surveillance intervals established to maintain instrument accuracy and regulatory compliance. Industry operating experience has shown that many instruments exhibit minimal drift between calibration cycles, resulting in a large percentage of calibrations that confirm acceptable performance without identifying meaningful degradation. These activities tend to introduce avoidable operational costs, increase outage scope, create additional maintenance workload, increase radiation exposure, and introduce the potential for maintenance- and infant mortality-induced errors.
Condition-based calibration approaches using online monitoring (OLM), historical data, and instrumentation performance analytics to evaluate sensor health and justify calibration interval extensions are based on actual equipment condition rather than fixed time intervals. Online monitoring continuously or periodically evaluates instrument performance using plant process data, while historical calibration analysis uses as-found/as-left (AFAL) calibration results and statistical drift evaluations to support engineering-based interval extensions. These approaches allow utilities to reduce unnecessary calibrations while maintaining confidence in instrument performance and regulatory compliance.
Implementation approaches may include vendor-supported monitoring programs with continuous analytics and structured reporting, or utility-insourced engineering evaluations using historical calibration data and utility-specific monitoring processes. Previous industry implementations have demonstrated significant reductions in planned calibration activities, reduced outage scope, and improved maintenance efficiency through the application of condition-based calibration.
Benefits
Benefits Estimate
Level 2 - Savings is greater than $1 million but less than $5 million per year (inclusive).
Benefits Description
Extending calibration intervals provide:
- Labor reduction
- Outage scope reduction
- Reduced maintenance- and infant mortality-induced errors
- Reduced contractor support
- Improved maintenance planning efficiency
Costs and Schedule
Cost
Level 3 - Implementation cost is less than $1 million (inclusive). Costs for additional units may be reduced if drift adjustments can be leveraged for multiple component types.
Schedule
One to Three Years
Scope Context
Per site cost and schedule estimates include labor associated with:
- Drift evaluations for numerous groups of instruments
- Calculation changes
- License amendment request for changes to tech spec surveillance frequency control program (SCFP)
- Work mechanism updates
Risks
- Cybersecurity and IT/OT changes and integration requirements
- Data quality and availability
- Regulatory concerns and changes
- Monitoring models, analytical tools, and workflow changes requiring continued validation, configuration control, and engineering oversight
- Long-term dependency on one specific vendor
- Risk of pricing changes
- Risk of availability
SWEEP Score
| Category | Level | Description |
|---|---|---|
| Cost | 3 | Implementation cost is less than $1 million (inclusive). |
| Savings | 2 | Savings are greater than $1 million per year but less than $5 million per year (inclusive). |
| Payback | 2 | Payback period is greater than one year but less than five years (inclusive). |
| Technical Readiness | 3 | The technology is ready for wide operational deployment. |
| Licensing Readiness | 3 | No changes are required for implementation. |
| Implementation Proficiency | 3 | The technology can be implemented by all sites, regardless of digital experience. |