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U.S. Department of Energy
Office of Scientific and Technical Information

Technology-Enabled Risk-Informed Maintenance Strategy to Minimize Operation and Maintenance Costs

Technical Report ·
DOI:https://doi.org/10.2172/1668402· OSTI ID:1668402

The domestic fleet of nuclear power plants (NPPs) is facing a unique economic sustainability challenge in today’s energy market due to high total operating costs. One of the major contributors to the total operating cost of an NPP is the operations and maintenance (O&M) budget, which includes labor-intense preventive maintenance (PM) programs. PM programs involve manually performing inspection, calibration, testing, and maintenance of plant assets at periodic frequencies, as well as time-based replacement of assets, irrespective of individual asset condition. This approach, combined with the push to achieve high capacity factors, has resulted in a labor-centric business model. It is time to transition from this labor-centric business model to a technology-centric business model that will enable an optimal maintenance strategy by eliminating unnecessary costs associated with time-based PM activities. To enable this transition, the commercial nuclear industries are utilizing and developing reliable methodologies, based on available state of the art technologies, which facilitate assessing equipment condition and the dynamic risk of failure. The U.S. Department of Energy’s Idaho National Laboratory (INL) under the Light Water Reactor Sustainability (LWRS) Program is partnering with PKMJ Technical Services and Public Service Enterprise Group (PSEG) Nuclear, LLC to develop and demonstrate a deployable risk-informed predictive maintenance strategy to eliminate unnecessary O&M costs for an identified plant system, laying the foundation for scale-up to the entire plant. Recently developed technologies such as advanced wireless and wired sensors, data analytics, and risk assessment methodologies will support this transition. The technology-centric O&M model will result in significant automation and lay the foundation for real-time condition assessment of plant assets, thus enabling condition-based maintenance and enhancing plant safety, reliability, and economics of operation.

Research Organization:
Idaho National Laboratory (INL), Idaho Falls, ID (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
DOE Contract Number:
AC07-05ID14517
OSTI ID:
1668402
Report Number(s):
INL/EXT--19-55169
Country of Publication:
United States
Language:
English