Improving an IoT-Based Motor Health Predictive Maintenance System Through Edge-Cloud Computing

Author(s):  
Kristine-Clair Lee ◽  
Christian Villamera ◽  
Carlos Adrian Daroya ◽  
Paolo Samontanez ◽  
Wilson M. Tan
Seikei-Kakou ◽  
2021 ◽  
Vol 33 (2) ◽  
pp. 54-56
Author(s):  
Tasuku Okimoto

Author(s):  
El-Adawi S. El-Mitwally ◽  
M. A. Rayan ◽  
N. H. Mostafa ◽  
Yehia M. Enab

Abstract At the present time, the maintenance of the equipment becomes an essential task for any production system. This task is becoming more important from both the quantity and the quality points of view, particularly in developing countries. Initiating a maintenance system controlled by the computer will be valuable and effective. The developed expert system is a combination of an intelligent inference engine matched with a database of information. This system will enable the operator to spot instantaneously the parameters of interest. The expert maintenance system will be designed to perform preventive maintenance tasks and detects faults/failure during the operating cycle. Predictive maintenance enables the operator to minimize the shut down time of faulty equipment and hence increases the productivity. Furthermore, the system will minimize the probable human faults and reduce production costs.


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