Using statistical models for optimal packaging in semiconductor manufacturing processes

Pub Date : 2024-08-07 DOI:10.1007/s42952-024-00284-1
Dongguen Kim, Heejin Kim, Yejin Kim, Minwoo Chae, Young Myoung Ko, Young-Mok Bae, Hyungsub Sim, Young Chan Oh, Keum Hwan Noh
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Abstract

The importance of the back-end process in semiconductor manufacturing has recently received significant attention from global manufacturers. The analysis of manufacturing data often provides crucial insights into problems inherent in the manufacturing processes. An important goal of the back-end process is to improve the yield of final products, called packages. A simple way to achieve this goal is to characterize low-quality wafers based on the analysis of manufacturing data and discard them before proceeding to the packaging step. Alternatively, this paper proposes a novel packaging method that significantly improves the package yield using statistical models scoring the quality of dies. We prove that the proposed packaging method is optimal and conduct thorough numerical experiments, showing its superiority.

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使用统计模型优化半导体制造工艺中的封装
后端流程在半导体制造中的重要性最近受到了全球制造商的极大关注。对制造数据的分析往往能提供对制造过程中固有问题的重要见解。后端工艺的一个重要目标是提高最终产品(即封装)的产量。实现这一目标的一个简单方法是根据制造数据分析确定低质量晶片的特征,并在进入封装步骤之前将其丢弃。作为替代方案,本文提出了一种新颖的封装方法,利用统计模型对模具质量进行评分,从而显著提高封装产量。我们证明了所提出的封装方法是最优的,并进行了全面的数值实验,证明了其优越性。
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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