Western Digital Technologies, Inc.

Austin Striegel

Timothy G Lieber

Robert Lester

Evan Richardson

Donald Penza

Gary Allan Herbst

Chuanwen Ji

Jared Tesone

Jim French

A data storage device comprises a disk having a plurality of data tracks and a plurality of servo wedges wherein the plurality of servo wedges comprise a plurality of wedge repeatable runout (WRRO) fields configured to store a plurality of WRRO compensation values in connection with the plurality of data tracks. The data storage device may also include a read/write head configured to be actuated over the disk, and a controller configured to gather position error signal (PES) data needed for computation of the WRRO compensation values during a field operation of the data storage device. The data storage device may be further configured to adjust a position of the read/write head based on the WRRO compensation values.

Data storage device integrating wedge repeatable runout (WRRO) learning into data recovery procedure (DRP)

An approach to identifying poorly performing data storage devices (DSDs) in a data storage system, such as hard disk drives (HDDs) and/or solid-state drives (SSDs), involves retrieving and evaluating a respective set of log pages, such as SCSI Log Sense counters, from each of multiple DSDs. Based on each respective set of log pages, a value for a Quality of Service (QoS) metric is determined for each respective DSD, where each QoS value represents an average percentage of bytes processed without the respective DSD performing an autonomous error correction. In response to a particular DSD reaching a predetermined threshold QoS value, an in-situ repair may be determined for the particular DSD or the particular DSD may be added to a list of candidate DSDs for further examination, which may include an FRPH examination for suitably configured DSDs.

Use of error correction-based metric for identifying poorly performing data storage devices

An approach to identifying problematic data storage devices, such as hard disk drives (HDDs), in a data storage system involves retrieving and evaluating a respective recovery log, such as a media error section of a device status log, from each of multiple HDDs. Based on each recovery log, a value for a Full Recoveries Per Hour (FRPH) metric is determined for each read-write head of each respective HDD. Generally, the FRPH metric characterizes the amount of time a head has spent performing recovery operations. In response to a particular head FRPH reaching a pre-determined threshold value, an in-situ repair can be determined for the HDD in which the head operates. Similarly, in the context of solid-state drives (SSDs), a latency metric is determinable based on time spent waiting on resolving input/output (IO) request collisions, on which an in-situ repair can be based.

Use of recovery behavior for prognosticating and in-situ repair of data storage devices

Non-limiting examples of the present disclosure relate to execution of in-situ manufacturing for a data storage device. In-situ manufacturing is on-location configuration of a data storage device within an operational environment in which a data storage device is being deployed. In-situ manufacturing occurs at any point after a data storage device is shipped from a manufacturing plant or factory. When an operational environment of the data storage device is known, parameters of the data storage device can be configured (or re-configured) on-location within an operational environment to optimize capacity management as well as performance of the data storage device.

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Rochester, MN, United States of America

Austin Striegel