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Application of multi-fidelity simulation modelling to integrated circuit packaging

机译:多保真度仿真建模在集成电路封装中的应用

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摘要

In semiconductor manufacturing, time-to-market is critical to maintain a competitive advantage through achieving customer satisfaction. Inefficient ways of utilising production resources will lead to a long cycle time. Therefore, machine allocation becomes an essential production decision in many practical manufacturing systems, especially for integrated circuit (IC) packaging. IC packaging is the process of encasing the finished die in a package in order to prevent corrosion and physical damage. Advanced IC packaging techniques add even more complexity into the production system, so reliable average cycle time of this complex system becomes difficult to obtain. We propose a new simulation optimisation framework with multi-fidelity models to study an IC packaging case of the machine allocation problem to pursue a minimum average cycle time. This framework consists of two methodologies: ordinal transformation (OT) and optimal sampling (OS). The OT first employs the low-fidelity model to fast observe all designs, and extracts insightful information from this model by transforming the original design space into an ordinal space. It follows that OS efficiently allocates the computing budget for searching the best design via high-fidelity simulations. An empirical study based on real data was conducted to validate the practical viability of the proposed framework.
机译:在半导体制造中,上市时间对于通过获得客户满意度来保持竞争优势至关重要。利用生产资源的效率低下会导致较长的周期时间。因此,机器分配已成为许多实际制造系统中必不可少的生产决策,尤其是对于集成电路(IC)封装。 IC封装是将完成的芯片封装在封装中以防止腐蚀和物理损坏的过程。先进的IC封装技术进一步增加了生产系统的复杂性,因此很难获得这种复杂系统的可靠平均周期时间。我们提出了一个具有多保真度模型的新的仿真优化框架,以研究机器分配问题的IC封装案例,以寻求最小的平均循环时间。该框架包含两种方法:顺序转换(OT)和最佳采样(OS)。 OT首先采用低保真模型来快速观察所有设计,然后通过将原始设计空间转换为顺序空间来从该模型中提取有洞察力的信息。因此,OS可以有效地分配计算预算,以通过高保真仿真来搜索最佳设计。进行了基于真实数据的实证研究,以验证所提出框架的实际可行性。

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