Methods, devices, and systems for reducing device test time

    公开(公告)号:US10699193B2

    公开(公告)日:2020-06-30

    申请号:US15833135

    申请日:2017-12-06

    Abstract: A method for testing and grading electronic devices includes receiving a set of testing data associated with an electronic device that is following a testing routine. Based on the set of testing data, the method includes computing a first performance metric of the electronic device by using a first artificial neural network and computing a second performance metric of the electronic device by using a second artificial neural network. Based on at least the first predicted performance metric and the second predicted performance metric, the method includes computing a grade for the electronic device.

    Variable speed data storage device testing system
    6.
    发明授权
    Variable speed data storage device testing system 有权
    变速数据存储设备测试系统

    公开(公告)号:US09552846B1

    公开(公告)日:2017-01-24

    申请号:US15141178

    申请日:2016-04-28

    Inventor: Teck Khoon Lim

    CPC classification number: G11B27/36 G11B19/048 G11B20/1816

    Abstract: A data storage device can be tested while spinning at a variety of different speeds. Data may be written to a data sector with a transducing head while at least one disk of a data storage device spins about a spindle at a default speed. One or more tests can subsequently be executed on the disk by reading servo data stored on the disk while the disk spins at a test speed that is greater than the default speed.

    Abstract translation: 可以在以各种不同速度旋转的同时测试数据存储设备。 数据可以用转换头写入数据扇区,而数据存储设备的至少一个盘以默认速度旋转主轴。 随后,当磁盘以大于默认速度的测试速度旋转时,通过读取存储在磁盘上的伺服数据,可以在磁盘上执行一个或多个测试。

    METHODS, DEVICES, AND SYSTEMS FOR REDUCING DEVICE TEST TIME

    公开(公告)号:US20190171940A1

    公开(公告)日:2019-06-06

    申请号:US15833135

    申请日:2017-12-06

    Abstract: A method for testing and grading electronic devices includes receiving a set of testing data associated with an electronic device that is following a testing routine. Based on the set of testing data, the method includes computing a first performance metric of the electronic device by using a first artificial neural network and computing a second performance metric of the electronic device by using a second artificial neural network. Based on at least the first predicted performance metric and the second predicted performance metric, the method includes computing a grade for the electronic device.

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