Causal inference for early detectection of hardware failure
Yang, Alan
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https://hdl.handle.net/2142/100049
Description
Title
Causal inference for early detectection of hardware failure
Author(s)
Yang, Alan
Contributor(s)
Rosenbaum, Elyse
Issue Date
2018-05
Keyword(s)
hardware failure detection
predicting hard disk drive failures
information theoretic measures
Abstract
Many modern hardware systems are equipped with sensors which record
time-series diagnostic data. These sensors enable data-driven failure prediction
that can reduce the need for component redundancy and lengthen
lifetime specifications, by allowing for identification and proactive replacement
of a soon-to-fail component. In this work, we develop a causal inference
framework for predicting data center hard disk drive failures using
multivariate time series recordings of temperature, read error rate, and other
attributes. Information-theoretic measures are developed to quantify relationships
between sensor variables, select prognostic features, and train a
predictor. Finally, a recurrent neural network demonstrating high predictive
accuracy and a low false alarm rate is developed, using field data collected
from an operating data center.
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