Cisco Technology, Inc.

Dao-I Tony Lin

Jie Xue

ShiJie Wen

James Edwin Turman

Anthony Winston

Zoe Frances Conroy

An approach is presented herein to use an in-situ algorithmic decision methodology during each stage of testing before 2C/4C to decide how long to test, how much margin should be used for each device under the test (DUT) to shorten or eliminate 2C/4C testing. Each DUT will be tested differently based on the risk level or the likelihood of failure at 2C/4C. To be able to achieve this, low-level hardware (HW) based sensors (on the printed circuit board assembly (PCBA), in power module, in silicon components, in silicon component complex, etc.) are used to collect telemetry data with a high frequency data acquisition rate during the testing. As testing is ongoing for each DUT, a margin distribution and algorithm modeling is performed in-situ.

Telemetry-based model driven manufacturing test methodology

A method, computer system, and computer program product are provided for stress-testing electronics using telemetry modeling. Telemetry data is received from one or more devices under test during a hardware testing phase, the telemetry data including one or more telemetry parameters. The telemetry data is processed using a predictive model to determine future values for the one or more telemetry parameters. Additional hardware testing is performed, wherein the additional hardware testing includes adjusting one or more testing components based on the determined future values.

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Pleasanton, CA, United States of America

Dao-I Tony Lin