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The U.S. commercial nuclear industry is facing increasing economic pressure due to low-cost alternatives such as natural gas combined-cycle combustion power plants and renewable energy technologies such as wind and solar. More efficient and intelligent operations and maintenance strategies can yield substantial economic gains through a proposed risk-informed predictive maintenance strategy. The strategy leverages plant process, maintenance, and vibration data with advanced data analytics to monitor and predict condition degradations in support of preventative maintenance. This paper documents the operating experience review of the existing monitoring and diagnostic process. A semi-structured series of interviews assessed current practices, tools, shortcomings, and anlaysts’ needs to support the development of a human system interface (HSI) for the advanced data analytics approach. The results of the interviews are reported as feature requirements for the proposed HSI system which is actively under development as part of this ongoing project.

Nuclear Operating Experience Review and User Needs Assessment for a Risk-informed Predictive Maintenance Human System Interface