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Predictive maintenance by ferrography
Wear, 1977Abstract Ferrography is a technique by which wear debris and contaminant particles are separated from a lubricant and analysed. The apparatus used and complementary investigational techniques are described. The use of Ferrography for machinery condition monitoring to prevent failure and to allow a safe change from expensive periodic dismantling of ...
D. Scott, V.C. Westcott
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2018
Industry 4.0 includes the connection of cybernetic and physical systems and the use of the Internet of things and services in all business and manufacturing processes of any company. According to recent research and studies, maintenance is one of the areas where significant effects of digitization and Industry 4.0 are expected. The results of the first
Brnadić, Tomislav +2 more
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Industry 4.0 includes the connection of cybernetic and physical systems and the use of the Internet of things and services in all business and manufacturing processes of any company. According to recent research and studies, maintenance is one of the areas where significant effects of digitization and Industry 4.0 are expected. The results of the first
Brnadić, Tomislav +2 more
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SPE Intelligent Energy International, 2012
Abstract Predictive Asset Maintenance - The Business Challenge Asset intensive industries such as Energy, Oil & Gas are continuously challenged to mitigate the risk of equipment failure to avoid unplanned costs, impacts on production, safety and environmental implications.
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Abstract Predictive Asset Maintenance - The Business Challenge Asset intensive industries such as Energy, Oil & Gas are continuously challenged to mitigate the risk of equipment failure to avoid unplanned costs, impacts on production, safety and environmental implications.
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Intelligent Predictive Maintenance System
2017The machine learning techniques can be efficiently used for optimal maintenance decision making. Currently, most of the companies and manufactures possess huge amounts of sensor, process, and environment data. Combining the data with the information about the failures succeeds in creating useful train data sets for predictive maintenance purposes.
Mateusz Marzec +3 more
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