Preventive Maintenance for Fault Detection in Transfer Nodes using Machine Learning
Joanita Dsouza, Senthil Velan · 2019
Preventive Maintenance is the new buzzword to upkeep an enterprise application in a real world scenario. It has also become a necessity to predict the faults that could occur between the different transfer nodes of the enterprise application. The features of preventive maintenance which includes methodical study, estimation, the notion of time, the diagnosis of faults and so on can be analyzed using well designed and structured methods of relevance to the application domain. In this scenario, the technologies which are focused are diagnosis of faults and activities, prediction of the states and monitoring the conditions. There is a large amount of data which is being used for preventive maintenance. The flow of packets between transfer nodes can be stored and this data can be used for purpose of training and testing. Further, machine learning algorithms can be implemented based on the features present in the historical data. The advantage on the study of preventive maintenance is that it can aid in reduction of cost which is the primary motive of each organization existing toady. By doing so the results can be applied to various organizations to resolve failures that could possibly occur in the future well in advance. This paper explains the application of machine learning algorithms for the detection of fault in transfer noted using preventive maintenance in an organization.