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Scientific Article details

Title Predictive Maintenance for Remanufacturing Based on Hybrid-Driven Remaining Useful Life Prediction
ID_Doc 16741
Authors Zhang, M; Amaitik, N; Wang, ZZ; Xu, YC; Maisuradze, A; Peschl, M; Tzovaras, D
Title Predictive Maintenance for Remanufacturing Based on Hybrid-Driven Remaining Useful Life Prediction
Year 2022
Published Applied Sciences-Basel, 12, 7
DOI 10.3390/app12073218
Abstract Remanufacturing is an activity of the circular economy model whose purpose is to keep the high value of products and materials. As opposed to the currently employed linear economic model, remanufacturing targets the extension of products and reduces the unnecessary and wasteful use of resources. Remanufacturing, along with health status monitoring, constitutes a key element for lifetime extension and reuse of large industrial equipment. The major challenge is to determine if a machine is worth remanufacturing and when is the optimal time to perform remanufacturing. The present work proposes a new predictive maintenance framework for the remanufacturing process based on a combination of remaining useful life prediction and condition monitoring methods. A hybrid-driven approach was used to combine the advantages of the knowledge model and historical data. The proposed method has been verified on the realistic run-to-failure rolling bearing degradation dataset. The experimental results combined with visualization analysis have proven the effectiveness of the proposed method.
Author Keywords circular economy; remanufacturing; predictive maintenance; condition monitoring; remaining useful life prediction; dynamic maintenance scheduling
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Science Citation Index Expanded (SCI-EXPANDED)
EID WOS:000790639400001
WoS Category Chemistry, Multidisciplinary; Engineering, Multidisciplinary; Materials Science, Multidisciplinary; Physics, Applied
Research Area Chemistry; Engineering; Materials Science; Physics
PDF https://www.mdpi.com/2076-3417/12/7/3218/pdf?version=1647936221
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