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Study of Reliability Analysis Based Power Generation Facilities Maintenance System - Focused on Continuous Ship Unloader -

신뢰성 분석 기반 발전설비 점검계획 수립 시스템 연구- 석탄 하역기를 중심으로 -

  • Hwang Seong Hwan (Department of Industrial Engineering, Inha University) ;
  • Kim Yu Rim (Department of Industrial Engineering, Inha University) ;
  • Kang Sung Woo (Department of Industrial Engineering, Inha University)
  • 황성환 (인하대학교 산업경영공학과) ;
  • 김유림 (인하대학교 산업경영공학과) ;
  • 강성우 (인하대학교 산업경영공학과)
  • Received : 2023.05.04
  • Accepted : 2023.06.16
  • Published : 2023.06.30

Abstract

Purpose: Recently, research has continued to predict the time of failure of the facility through measurement data obtained by attaching a sensor to the facility. However, depending on the facility, it may be difficult to attach a sensor. The purpose of this study is to propose a power generation maintenance plan system based on failure record data obtained from Continuous Ship Unloader, one of the facilities that is difficult to attach sensors. Methods: This study uses data collected from 2012 to 2022 from the 'CSU-1B' model among Continuous Ship Unloader operated by Korea Midland Power Co., LTD. By fitting fault record data to the Weibull distribution, appropriate maintenance cycles and ranges for each target facility subsystem are derived. In addition, maintenance group between subsystems is selected through Euclidean distance, a metric often used for time series data similarity. Through this, a system for establishing an maintenance plan for power generation facilities is proposed. Results: The results of this study are as follows. For the 17 subsystems of the Continuous Ship Unloader, proper maintenance cycles and ranges were determined, and a total of four maintenance groups were chosen. This resulted in the creation of an power generation maintenance plan system and the establishment of an maintenance plan. Conclusion: This study is a case study of power generation facilities. We proposed a maintenance plan system for Continuous Ship Unloader among power generation facilities.

Keywords

Acknowledgement

이 성과는 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구임(No. 2022H1D8A3037396).

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