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Provocation tests, design of experiments and advanced statistical modeling to estimate product sensitivity to a defect: delamination failure case study for automotive semiconductors

机译:挑衅测试,实验设计和先进的统计建模,以估算产品敏感性对缺陷的敏感性:汽车半导体的分层失效案例研究

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During a short period, a malfunctioning happened on a manufacturing equipment in which about twenty semiconductor parts for automotive have been submitted on a process step. A same defect of inter-layer dielectric delamination was generated but each product showed different sensitivity to this defect. Failure that was generated was a latent one and occurred in field, which is fitting with the most serious situation for a final customer. Knowing how to predict quantity of failures expected to happen is very critical. Two semiconductor products for automotive have been specifically studied: the first one was a valve driver, the second one was an accelerometric sensor. Purpose was to highlight the main factors on sensitivity to defect. Was it possible to build a model from these factors to estimate sensitivity of any impacted product among the twenty ones ? For that, many technics have been implemented, from most typical reliability and provocation tests, until advanced design of experiments and modeling. Some strong results were obtained, as a model validated, but above all, in order to fully analyze a failure, to understand product sensitivity, and to assess risk, complementarity of typical reliability tests with advanced statistical technics was definitively proved.
机译:在短时间内,在制造设备上发生故障,其中已经在工艺步骤中提交了大约20个用于汽车的半导体部件。产生相同层间介电分层的缺陷,但每种产物对该缺陷表现出不同的敏感性。生成的失败是潜在的一个并发生在领域,这与最终客户的最严重情况合作。了解如何预测预期发生的失败数量非常关键。用于汽车的两个半导体产品已经专门研究:第一个是阀门驱动器,第二个是加速度传感器。目的是突出对缺陷敏感性的主要因素。是否有可能从这些因素中建立模型来估计二十多个受影响产品的敏感性?为此,从大多数典型的可靠性和挑衅测试中实现了许多技术,直到高级设计的实验和建模。获得了一些强劲的结果,作为验证的模型,但最重要的是,为了充分分析失败,了解产品敏感性,并评估风险,具有先进的统计技术的典型可靠性测试的互补性被明确证明。

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