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Development of web-based reliability data analysis algorithm model and its application

Authors
Hwang, Seok-WonOh, Ji-YongMoosung Jae
Issue Date
Feb-2010
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Citation
ANNALS OF NUCLEAR ENERGY, v.37, no.2, pp.248 - 255
Indexed
SCIE
SCOPUS
Journal Title
ANNALS OF NUCLEAR ENERGY
Volume
37
Number
2
Start Page
248
End Page
255
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/175509
DOI
10.1016/j.anucene.2009.10.015
ISSN
0306-4549
Abstract
For this study, a database model of plant reliability was developed for the effective acquisition and management of plant-specific data that can be used in various applications of plant programs as well as in Probabilistic Safety Assessment (PSA). Through the development of a web-based reliability data analysis algorithm, this approach systematically gathers specific plant data such as component failure history, maintenance history, and shift diary. First. for the application of the developed algorithm, this study reestablished the raw data types, data deposition procedures and features of the Enterprise Resource Planning (ERP) system process. The component codes and system codes were standardized to make statistical analysis between different types of plants possible. This standardization contributes to the establishment of a flexible database model that allows the customization of reliability data for the various applications depending on component types and systems. In addition, this approach makes it possible for users to perform trend analyses and data comparisons for the significant plant components and systems. The validation of the algorithm is performed through a comparison of the importance measure value (Fussel-Vesely) of the mathematical calculation and that of the algorithm application. The development of a reliability database algorithm is one of the best approaches for providing systemic management of plant-specific reliability data with transparency and continuity. This proposed algorithm reinforces the relationships between raw data and application results so that it can provide a comprehensive database that offers everything from basic plant-related data to final customized data.
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