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Condition Monitoring for Predictive Maintenance: - A Tool for Systems Prognosis within the Industrial Internet Applications

Chukwuekwe, Douglas Okafor
Master thesis
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URI
http://hdl.handle.net/11250/2404760
Date
2016
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  • Institutt for maskinteknikk og produksjon [2530]
Abstract
The acceptance of two peer-reviewed papers based on this study for presentation at two international conferences is a proof of the report's originality, solidity and informativity. The derived mathematical model for predicting the future vibration severity was based on single values which are compliant with the proposed Industry 4.0 reference architecture. The vibration data stored, processed and analysed in the compliant format helps to populate the big data which in turn is used for the data driven smart maintenance with a great descriptive accuracy, predictive powers and prescriptive capabilities. Through the use of case studies, the sub-objectives of the thesis were met. Condition monitoring was shown to be a safe cost cutting mechanism. The possible approaches that can be used to integrate vibration analysis with the Industrial Internet of Things were outlined in the context of smart maintenance.
Publisher
NTNU

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