Assessment of residual damage in leadfree electronics subjected to multiple thermal environments of thermal aging and thermal cycling

P. Lall, R. Vaidya, V. More, K. Goebel, J. Suhling
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引用次数: 16

Abstract

Electronic systems are often stored for long periods prior to deployment in the intended environment. Aging has been previously shown to effect the reliability and constitutive behavior of second-level leadfree interconnects. Deployed systems may be subjected to cyclic thermo-mechanical loads subsequent to deployment. Prognostication of accrued damage and assessment of residual life is extremely critical for ultra-high reliability systems in which the cost of failure is too high. The presented methodology uses leading indicators of failure based on microstructural evolution of damage to identify impending failure in electronic systems subjected to sequential stresses of thermal aging and thermal cycling. The methodology has been demonstrated on area-array ball-grid array test assemblies with Sn3Ag0.5Cu interconnects subjected to thermal aging at 125°C and thermal cycling from −55 to 125°C for various lengths of time and cycles. Damage equivalency methodologies have been developed to map damage accrued in thermal aging to the reduction in thermo-mechanical cyclic life based on damage proxies. Assemblies have been prognosticated to assess the error with interrogation of system state and assessment of residual life. Prognostic metrics including α-λ metric, sample standard deviation, mean square error, mean absolute percentage error, average bias, relative accuracy, and cumulative relative accuracy have been used to compare the performance of the damage proxies.
热老化和热循环等多种热环境下无铅电子产品的残余损伤评估
电子系统在部署到预期的环境之前,通常要存储很长时间。老化已经被证明会影响二级无铅互连的可靠性和本构行为。部署后的系统可能会受到循环热机械负荷的影响。对于失效成本过高的超高可靠性系统,累积损伤的预测和剩余寿命的评估是至关重要的。提出的方法使用基于损伤微观结构演变的主要失效指标来识别受热老化和热循环顺序应力影响的电子系统即将发生的失效。该方法已在具有Sn3Ag0.5Cu互连的区域阵列球栅阵列测试组件上进行了验证,测试组件在125°C下进行了热老化,并在- 55至125°C之间进行了不同长度的时间和周期的热循环。损伤等效方法已经被开发出来,将热老化过程中累积的损伤映射到基于损伤代理的热-机械循环寿命的减少。通过对系统状态的询问和剩余寿命的评估,对装配进行了预测,以评估误差。预后指标包括α-λ度量、样本标准差、均方误差、平均绝对百分比误差、平均偏差、相对精度和累积相对精度,用于比较损害代理的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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