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Multi-objective decision support system in numerical reliability optimization of modern electronic packaging

机译:现代电子包装数值可靠性优化的多目标决策支持系统

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Nowadays, numerical prototyping methods in electronic packaging are widely used. This is mainly due to cost and time reduction and improved functionality and reliability of final products. Recently, there has been a lot of interest and work conducted on advanced numerical optimization, which can be directly applied to prototyping. So far, the optimization is focused on one criteria while neglecting problem of multi-objectivity, which is not the best approach from practical point of view. Nevertheless, such an approach is jusitified from the point of view of complex analysis, interdisciplinary issues and reduced accuracy of numerical models. In reality, there are usually many criteria which, in order to solve the problem, have to be taken into consideration. There are many multi-objective methods, of which the Pareto set approach is mostly cited in the literature. The “problem” of multi-objective optimization is that not a single optimal solution has resulted but the set of equivalent optimal solutions. This set of equivalent optimal solutions is referenced as “the Pareto set”. From the mathematical point of view, every value from this set can be treated as optimal for certain assumed constraints. However, there could be some additional conditions which cannot be applied to optimization process and some of the results from the Pareto set are more likely (i.e., the fabrication process will be more repeatable) then the others. So, the question is: which value from the Pareto set should be taken to further processing? There are two possibilities: asking an expert for the advice or use the decision making system. Decision making methods based on multi-objective optimization could be referenced as “Multiple criteria decision making” (MCDM) or “Multiple criterial decision aid” (MCDA) systems. There are several groups of these methods: (a) mathematical multi-objective programming, (b) artificial intelligence methods, (c) simple arithmetic methods, and (d) advanced mathematical methods. The current paper will focus on designing and application of the decision support system for multi-objective numerical reliability optimization of electronic packaging. The work will be based on the self developed numerical tool based on Python Scrippting language and will present its application to selected microelectronic packages based on its numerical model elaborated in ABAQUS.
机译:如今,电子包装中的数字原型方法被广泛使用。这主要是由于成本和时间的减少以及最终产品功能和可靠性的提高。最近,人们对高级数值优化产生了浓厚的兴趣并进行了工作,这些数值优化可以直接应用于原型制作。到目前为止,优化只关注一个标准,而忽略了多目标性问题,从实际的角度来看,这并不是最佳方法。然而,从复杂分析,跨学科问题和降低数值模型的准确性的角度来看,这种方法是合理的。实际上,为了解决该问题,通常有许多标准必须考虑在内。有许多多目标方法,其中Pareto集合方法在文献中最多被引用。多目标优化的“问题”在于,不是一个单一的最优解,而是一组等效的最优解。这套等效的最优解被称为“帕累托集”。从数学角度来看,对于某些假定的约束条件,该集合中的每个值都可以视为最佳值。但是,可能存在一些其他条件无法应用于优化过程,并且帕累托集的某些结果比其他条件更有可能(即制造过程更具可重复性)。因此,问题是:应该将帕累托集合中的哪个值用于进一步处理?有两种可能性:向专家寻求建议或使用决策系统。基于多目标优化的决策方法可以称为“多准则决策”(MCDM)或“多准则决策辅助”(MCDA)系统。这些方法有几类:(a)数学多目标编程,(b)人工智能方法,(c)简单算术方法,以及(d)高级数学方法。本文将重点研究用于电子包装的多目标数值可靠性优化的决策支持系统的设计和应用。这项工作将基于基于Python Scrippting语言的自行开发的数值工具,并将基于ABAQUS阐述的数值模型将其应用于选定的微电子封装。

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  • 来源
    《Microsystem Technologies》 |2009年第12期|1777-1783|共7页
  • 作者单位

    Faculty of Microsystem Electronics and Photonics Wrocław University of Technology ul. Długa 65 53-633 Wrocław Poland;

    Faculty of Microsystem Electronics and Photonics Wrocław University of Technology ul. Długa 65 53-633 Wrocław Poland;

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