PSAM 16 Conference Paper Overview
Welcome to the PSAM 16 Conference paper and speaker overview page.
Lead Author: Diego Mandelli Co-author(s): C. Wang: Congjian.Wang@inl.gov
S. Lawrence: Svetlana.Lawrence@inl.gov
D. Morton: david.morton@northwestern.edu
I. Popova: ivilina.popova@gmail.com
S. Hess: SHess@jensenhughes.com
| Bridging equipment reliability data and risk informed decisions in a plant operation context |
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| 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. The Risk-Informed Asset Management (RIAM) project is tasked to develop tools in support of the equipment reliability and asset management programs at nuclear power plants. These tools are designed to create a direct bridge between component health/lifecycle data and decision making (e.g., maintenance scheduling and project prioritization). The goal of this article is to provide a guide for specific use cases that the RIAM project is targeting. We have grouped uses cases into three main areas. The first area focuses on the analysis of equipment reliability data with a particular emphasis on condition-based data, such as test/surveillance reports and component monitoring data. The second area focuses on the integration of equipment reliability into system/plant reliability models to determine system/plant health and identify the components that are critical to maintain an operational system. Lastly, the third area manages plant resources, such as maintenance activities and replacement scheduling using optimization methods. Here the primary focus is on supporting typical system engineer decisions regarding maintenance activity scheduling and component aging management. This is performed in a risk-informed context where 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. |
Paper DI118 Preview
Author and Presentation Info
Lead Author Name: Diego Mandelli (diego.mandelli@inl.gov)
Bio:
Country: United States of America
Company: Idaho National Laboratory
Job Title: R&D Scientist
Bio:
Country: United States of America
Company: Idaho National Laboratory
Job Title: R&D Scientist