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Remanufacturing Decision-Making for Gas Insulated Switchgear with Remaining Useful Life Predictionopen access

Authors
Moon, SeokhoCho, HansamKoh, EunjiCho, Yong SungOh, Hyoung LokKim, YounghoonKim, Seoung Bum
Issue Date
10월-2022
Publisher
MDPI
Keywords
remanufacturing; gas-insulated switchgear; remaining useful life regression; accelerated life testing; replacement simulation
Citation
SUSTAINABILITY, v.14, no.19
Indexed
SCIE
SSCI
SCOPUS
Journal Title
SUSTAINABILITY
Volume
14
Number
19
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/145491
DOI
10.3390/su141912357
ISSN
2071-1050
Abstract
Remanufacturing has emerged as a way to solve production problems, as raw material costs increase and environmental pollution caused by discarded equipment occurs. The process can extend product lifetime and prevent waste of resources. In particular, it has economical efficiency for large equipment such as GIS (Gas Insulated Switchgear). The crucial points in remanufacturing are determining replaceable parts and economic valuation. To address these issues, we propose a framework for remanufacturing GIS with remaining lifetime prediction. We construct a regression model for remaining useful life (RUL) in the proposed framework using GIS sensor data. The cost of the replacement parts is estimated with the selected sensors. To validate the effectiveness of the proposed framework, we conducted accelerated life testing on a GIS for data acquisition and applied our framework. The experimental results demonstrate that the tree-based RUL regression model outperforms the others in prediction accuracy. In the simulation of part replacement, the important sensor-based decision-making improves RUL significantly.
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