A market-oriented wafer map optimization methodology using Differential Evolution to maximize wafer productivity

Jong-Seong Kim, C. Ahn, Tae-Woo Kim, Hyun-Jin Lee, Jong-Bae Lee
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引用次数: 4

Abstract

In order to have a competitive edge in increasing global competition, memory industries need to improve productivity by a novel manufacturing strategy which is apposite to the rapid market changes. However, the conventional wafer productivity model only focuses on maximizing gross die which cannot address wafer productivity for profitability, i.e. return on investment (ROI), with respect to current market situations, since ROI is significantly influenced not only by the number of gross dies, but also by the number of shots and the market price. In this paper, we propose a novel productivity model based on ROI in order to compare wafer maps and to determine a chip size for productivity. To search the productivity-maximal wafer map in extremely large search space, we adopt Differential Evolution (DE) as the optimization technique. The computational results show that the proposed method can solve the problem of optimizing wafer map in minutes. Comparison results have demonstrated that the proposed method effectively improved wafer productivity by up to 1.82% in contrast with the old method. Ultimately, the proposed approach helps memory design engineers determine a chip size in an early design stage with consideration of the corresponding productivity.
一种以市场为导向的晶圆图优化方法,使用差分进化来最大化晶圆生产效率
为了在日益激烈的全球竞争中获得竞争优势,存储产业需要通过一种新的制造策略来提高生产率,以适应快速变化的市场。然而,传统的晶圆生产率模型只关注最大化总晶圆,而不能解决晶圆生产率的盈利能力,即投资回报率(ROI),相对于当前的市场情况,因为ROI不仅受到总晶圆数量的显著影响,还受到射击次数和市场价格的显著影响。在本文中,我们提出了一种新的基于ROI的生产率模型,以比较晶圆图并确定生产率的芯片尺寸。为了在极大的搜索空间中搜索生产率最大的晶圆映射,我们采用差分进化(DE)作为优化技术。计算结果表明,该方法可以在数分钟内解决晶圆图优化问题。对比结果表明,与旧方法相比,该方法有效地提高了晶圆生产率达1.82%。最终,所提出的方法可以帮助存储器设计工程师在考虑相应生产率的早期设计阶段确定芯片尺寸。
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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