OPTIMIZING PREDICTIVE MAINTENANCE FOR MAINTENANCE MANAGEMENT DEVELOPMENT: A HYBRID APPROACH USING VIBRATION AND SHOCK-PULSE MONITORING
DOI:
https://doi.org/10.71235/rmee.225Keywords:
Predictive maintenance, vibration analysis, shock-pulse monitoring, maintenance management, Industry 4.0.Abstract
The paper discusses an account of optimized predictive maintenance framework development and implementation towards better maintenance management in the industrial environment. The proposed study supports enhanced decision making, resource allocation, and fault detection through combining vibration analysis with shock-pulse monitoring. All data used were collected from rotating equipment at one European aluminum processing plant and analyzed by frequency-domain as well as shock-pulse techniques. The hybrid monitoring system results were more sensitive with lower false positives alarms than the normal vibration-based diagnosis. Integrated maintenance planning led to 30 % of unplanned downtime reduced and 12 % of total maintenance cost decreased. Apart from technical performance, this paper will show how predictive maintenance helps develop maintenance management by converting diagnostic data into useful managerial information. Predictive Maintenance is emphasized as a strategic component of Maintenance 4.0 supporting Reliability, Cost efficiency, and Sustainable Asset Management.
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Copyright (c) 2025 Geovana GOMES, Nicolae Stelian UNGUREANU, Gábor KALACSKÁ
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