Data plays a critical role in predictive maintenance for drives. It can be the key to averting drive failures. Monitoring data on drive health such as SMART (Self-Monitoring, Analysis, and Reporting Technology) attributes and temperature is an integral part of threshold-based predictive maintenance methods.

The backbone of threshold-based approaches is SMART. SMART attributes include information observed by the drive over the course of its operation, such as temperature, power-on hours, and reallocated sector count. Each SMART attribute may come with six pieces of data: a raw value, a normalized value, a threshold, a worst value, a pre-fail/advisory flag, and an online data collection flag.

The raw value is simply the raw value of the SMART attribute being measured. The normalized value is the SMART attribute scaled to some value between 1 and 253, where values greater than 100 are typically good, and higher values are typically better. The threshold is the normalized value below which a SMART attribute will indicate that it has been “tripped.”

While SMART trips are a good indicator that something is amiss, the lack of a SMART trip is not necessarily a good indicator that your drive is healthy. One reason is that the thresholds chosen for SMART trips are generally very conservative, meaning that it takes major problems for a SMART trip to go off. Another potential reason may be that SMART trips are not sensitive to health changes that occur over time. For example, a SMART 5 (reallocated sector count) trip is based on the latest value of reallocated sector count, but it does not take into account the way that the value changes over time, which can be pertinent to the drive’s health.

Even though SMART attributes are not always standardized for predicting drive failure, they have often been used to train AI algorithms that predict drive failures.

ULINK DA Drive Analyzer uses algorithms to analyze SMART and other drive health parameters to look for patterns in a drive’s health indicators over time. It provides users with a centralized online dashboard for viewing their drives’ health data from multiple systems. It provides critical tools and insights necessary to predict and minimize drive failures.

When the ULINK DA identifies potential issues or deteriorating drive health, it promptly sends alerts and warnings to administrators. This enables proactive planning for maintenance and replacements and minimizes the risk of data loss and system downtime.


QNAP and ULINK Release DA Drive Analyzer, AI-powered Drive Failure Prediction Tool for NAS

Photo Credit: Svitlana Hulko