Early Concepts for the Coupling of a Nuclear Plant Computer to a Computerized Maintenance Management System for Autonomous Prognostic Model Development

Zachary Welz, J. Wesley Hines, and Belle R. Upadhyaya
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phmc_15_026.pdf457.59 KBAugust 3, 2015 - 6:42am

Large amounts of process data are continuously recorded in a variety of industries. For nuclear power plants, these data are stored within the plant computer. As parts begin to degrade and components fail, maintenance personnel are responsible for making repairs and recording these repairs in a computerized maintenance management system (CMMS). Unique prognostic methods can be used to increase knowledge about the degradation of the system and provide accurate predictions of remaining useful life (RUL) before the system reaches an undesirable level of operation. These lifecycle prognostic models require important data that are stored within the CMMS and plant computer. This paper outlines a concept that uses data mining based on Big Data efforts in order to couple the plant computer data with the CMMS so that prognostic information can be gathered and analyzed. Once the plant computer and CMMS are coupled, important divisions of failure data can be mined out and used to update or build prognostic models based on component failure times, stressor information, and signal/residual values. An effective implementation of this concept means that the results could be used as a priori prognostic information in lifecycle prognostic models.

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Health management system design and engineering
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