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Robust optimization design of 3D MCM packages for reducing warpage under uncertainty

机译:3D MCM封装的鲁棒优化设计,可减少不确定性下的翘曲

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One critical issue for manufacturing 3D MCM packages is the warpage induced during the process. The effects of several important parameters, including processing conditions, package geometry and materials, are specifically studied on the occurrence of warpage and optimized to reduce the warpage in many previous literatures. However, the design parameter values are not always precisely known but can contain a level of uncertainty to some extent due to, for example manufacturing tolerance. In some case, the design parameters variations can not be neglected. In this paper, the effect of structure geometry tolerance and material property tolerance on package warpage robustness was took into account and analyzed. The robust optimization mathematic model of the 3D packages, considering the uncertainty of the design parameters, was built. And the robust optimization method based on the Monte-carlo simulations and Genetic Algorithm was present to solve the optimization problem above. Firstly, the parametric design finite element model of the specific 3D MCM package was built. Secondly, the statistic distribution of the warpage induced by the design parameters variations was obtained based on the Monte-carlo simulations. Finally, the GA was implemented to optimize the mean value and standard deviation of the warpage. The resulting robust optimization design shows that the robust optimization design is insensitive to variations on design variables within a feasible region.
机译:制造3D MCM封装的一个关键问题是在此过程中引起的翘曲。在许多先前的文献中,专门研究了翘曲的发生等几个重要参数的影响,包括加工条件,包装的几何形状和材料,并进行了优化以减少翘曲。然而,设计参数值并非总是精确地已知,而是由于例如制造公差而在某种程度上可以包含一定程度的不确定性。在某些情况下,不能忽略设计参数的变化。本文考虑并分析了结构几何公差和材料特性公差对包装翘曲鲁棒性的影响。考虑到设计参数的不确定性,建立了3D软件包的鲁棒优化数学模型。提出了一种基于蒙特卡洛模拟和遗传算法的鲁棒优化方法,以解决上述优化问题。首先,建立了特定3D MCM封装的参数化设计有限元模型。其次,基于蒙特卡洛模拟,获得了由设计参数变化引起的翘曲的统计分布。最后,采用遗传算法优化翘曲的平均值和标准偏差。最终的鲁棒优化设计表明,鲁棒优化设计对可行区域内设计变量的变化不敏感。

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