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DOE OSTI · 3027782

INTEGRATION OF DATA ANALYTICS WITH SYSTEM HEALTH PROGRAMS

Mandelli, Diego [Idaho National Laboratory] (ORCID:0000000293542233)·Wang, Congjian [Idaho National Laboratory] (ORCID:0000000207789927)
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Abstract

Industry equipment reliability and asset management programs are essential elements that help ensure the safe and economical operation of nuclear power plants. The effectiveness of these programs is addressed in several industry developed and regulatory programs. However, these programs have proven to be labor intensive and expensive. There is an opportunity to significantly enhance the collection, analysis, and use of this information to provide more cost-effective plant operation. Additionally, there is an acute industry need to leverage advanced technology to reduce costs and improve operational effectiveness. The goal of this paper is to provide effective and efficient analytical methods and tools to support risk-informed decisions for the equipment reliability and asset management programs at nuclear power plants. This is accomplished by creating a direct bridge between component health/lifecycle data and decision making (e.g., maintenance scheduling and project prioritization). Here we are supporting typical system engineer decisions regarding maintenance activity scheduling and component ageing management. This is performed in a risk-informed context where herein the term “risk” is broadly constructed to include both plant reliability and economics. This framework combines data analytics tools to analyze equipment reliability data with risk-informed methods designed to support system engineer decisions (e.g., maintenance and replacement schedules, optimal maintenance posture) in a customizable workflow. A challenge is that the structure of this workflow strongly depends on the decision that needs to be made, the type of data available, and the constraints that need to be considered. Current methods are designed to provide specific answers to specific problems; however, these methods might prove to be inadequate even when problem settings slightly change (e.g., different types of requirements, additional dependencies between system reliability and economics). We tackled this challenge by designing framework in a flexible and modular fashion such that the user can assemble and customize his/her own workflow that integrates SSC economic lifecycle models (e.g., maintenance and replacement costs), system reliability models, and optimization methods.

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97 - MATHEMATICS AND COMPUTINGdata analyticsdecision makinghealth management

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BibTeXRIS

Mandelli, Diego [Idaho National Laboratory] (ORCID:0000000293542233), Wang, Congjian [Idaho National Laboratory] (ORCID:0000000207789927). 2025-09-24. INTEGRATION OF DATA ANALYTICS WITH SYSTEM HEALTH PROGRAMS. https://www.osti.gov/biblio/3027782

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