Implementation of a Basic Predictive Maintenance Strategy to Reduce Downtime in Mechanical Equipment Using Statistical Analysis

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dc.contributor.advisorDeák , Krisztián
dc.contributor.advisorThabet, Amir
dc.contributor.authorJaballah, Aziz
dc.contributor.departmentDE--Műszaki Kar
dc.date.accessioned2026-06-02T12:09:50Z
dc.date.available2026-06-02T12:09:50Z
dc.date.created2026-05-05
dc.description.abstractThis thesis develops a basic predictive maintenance strategy for rotating mechanical equipment using simple statistical analysis of vibration data. It uses the PU‑MAFAULDA imbalance dataset to extract interpretable time‑domain features, mainly RMS, standard deviation, and trend measures, and shows how these can indicate abnormal machine behavior and gradual degradation. A validation study on simulated data compares static thresholds, adaptive thresholds, and trend‑based indicators, demonstrating that combining thresholds with trend detection provides earlier and more reliable fault warnings than fixed limits alone. Building on these results, the work proposes a maintenance scheduling framework that classifies machine condition into three health states normal, warning, and critical and assigns clear maintenance actions and response times to each state. The method is designed to be transparent, low‑cost, and suitable for small and medium‑sized companies that lack large historical datasets or advanced machine‑learning infrastructure. Overall, the thesis provides a practical path for moving from purely preventive maintenance towards a simple but effective predictive maintenance approach.
dc.description.courseMechanical Engineeringen
dc.description.degreeMSc/MA
dc.format.extent53
dc.identifier.urihttps://hdl.handle.net/2437/407688
dc.language.isoen
dc.rights.infoHozzáférhető a 2022 decemberi felsőoktatási törvénymódosítás értelmében.
dc.subjectmachine learning
dc.subjectpredictive maintenance
dc.subjectPredictive indicators
dc.subjectBearings
dc.subjectstatistical analysis
dc.subjectVibration DATA
dc.subject.dspaceEngineering Sciences
dc.titleImplementation of a Basic Predictive Maintenance Strategy to Reduce Downtime in Mechanical Equipment Using Statistical Analysis
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Theses (Department of Mechanical Engineering)