Remaining Useful Life Estimation of Hard Disk Drives based on Deep Neural Networks

Nowadays Hard Disk Drives (HDDs) are essential storage devices in most large-scale storage systems. As a consequence, HDD failures have severe effects that may range from data loss to service unavailability. Considering such scenario, academy and industry have driven its attention to HDDs failure prognostics solutions. In this work, we evaluate two of the most common deep learning architecture in the task of HDD failure prediction. Our tests were conducted on real-world datasets and the proposals were compared to a recurrent neural network. The results of this study showed that deep learning models are a valid alternative to solve this problem since they achieved good results and a significant amount of data is available.