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Thermal Environmental Stress Screen Optimization

机译:热环境应力筛选优化

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摘要

A multi parameter optimization process is created to minimize test time for thermal environmental stress screening (ESS), while meeting the minimum desired strength of screen level. The ESS variables affecting the test time include the maximum and minimum soak temperatures, the maximum and minimum overshoot temperatures, the dwell time at soak temperature, the dwell time at overshoot temperature, the thermal chamber ramp rate, and the number of ESS cycles. Factors affecting the hardware strength of screen include the total temperature range experienced by the hardware, the hardware thermal ramp rate, and the number of ESS cycles. The Matlab based optimization routine includes a two node thermal model to generate a thermal chamber temperature profile and a resulting hardware temperature response given the known time constant of the hardware under test. Additionally, the optimization process also includes custom functions that specify necessary constraints, the most important of which is the desired minimum precipitation efficiency of 88.7%. For the case study presented herein, the optimization process produces a significant reduction in necessary test time while maintaining the desired minimum precipitation efficiency. Actual test time improvements depend on many factors including the hardware time constant, strength of screen requirements, and thermal chamber capabilities. The primary purpose of this study is to demonstrate a process by which thermal environmental stress screening can be optimized.
机译:创建了一个多参数优化过程,以最小化用于热环境应力筛选(ESS)的测试时间,同时满足所需的最小筛选强度。影响测试时间的ESS变量包括最大和最小均热温度,最大和最小过冲温度,均热温度下的停留时间,过冲温度下的停留时间,热室升温速率以及ESS循环次数。影响屏幕硬件强度的因素包括硬件所经历的总温度范围,硬件热升温速率和ESS循环数。基于Matlab的优化例程包括一个两节点热模型,用于在给定被测硬件的已知时间常数的情况下生成热室温度曲线以及由此产生的硬件温度响应。此外,优化过程还包括指定必要约束条件的自定义函数,其中最重要的是所需的最低降水效率88.7%。对于本文介绍的案例研究,优化过程可显着减少必要的测试时间,同时保持所需的最小沉淀效率。实际测试时间的改善取决于许多因素,包括硬件时间常数,屏幕要求的强度和热室功能。这项研究的主要目的是演示可以优化热环境应力筛选的过程。

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