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

Remanufacturing has emerged as a way to solve production problems, raw material costs increase and environmental pollution caused by discarded equipment occurs. The process can extend product lifetime prevent waste of resources. In particular, it economical efficiency for large such GIS (Gas Insulated Switchgear). crucial points in remanufacturing are determining replaceable parts economic valuation. To address these issues, we propose framework with remaining prediction. We construct regression model useful life (RUL) the proposed using sensor data. cost replacement is estimated selected sensors. validate effectiveness framework, conducted accelerated testing on data acquisition applied our framework. experimental results demonstrate that tree-based RUL outperforms others prediction accuracy. simulation part replacement, important sensor-based decision-making improves significantly.