【摘要】：隨著中國政府推出《國家集成電路產(chǎn)業(yè)發(fā)展推進(jìn)綱要》后,集成電路制造產(chǎn)業(yè)在我國蓬勃發(fā)展。在我國,集成電路制造多以代工形式為主,因此對于產(chǎn)業(yè)發(fā)展與生存的關(guān)鍵在于集成電路芯片的良率控制與提高。在集成電路良率預(yù)測模型的研究上,從上世紀(jì)60年代開始就有學(xué)者提出各種良率模型,早期的研究主要集中在尋找良率和線上缺陷的關(guān)系。隨著工藝提升、設(shè)計(jì)難度增大,良率預(yù)測也希望能更精確。文中,我們提出良率損失的兩種模式。第一類良率損失模式,線上缺陷導(dǎo)致的良率損失。第二類良率損失模式,芯片工藝設(shè)計(jì)缺陷導(dǎo)致的良率損失。我們以電性測試參數(shù)為自變量,利用統(tǒng)計(jì)模型來精確預(yù)測良率損失的情況。通過建立兩類良率模式的多元分段函數(shù),嘗試用主成分分析法減少重復(fù)信息,用決策樹方法找到合適分段點(diǎn),并分別對分段部分建立Logistic回歸模型。根據(jù)模型分析的結(jié)果,發(fā)現(xiàn)此良率預(yù)測模型對誤差有很大的改善。而此多元分段模型,也解釋了兩種良率損失模型并存的現(xiàn)象�；诖朔椒�,可以將統(tǒng)計(jì)模型的構(gòu)建方式建立一套標(biāo)準(zhǔn)流程,并可以借用計(jì)算機(jī)程序?qū)⒋藰?biāo)準(zhǔn)自動化。便于一線工程師使用此工具,及時發(fā)現(xiàn)生產(chǎn)異常,減少損失。
[Abstract]:With the introduction of the National Integrated Circuit Industry Development Program by the Chinese government, the integrated circuit manufacturing industry has flourished in China. In China, the manufacturing of integrated circuits is mainly in the form of contract manufacturing, so the key to the development and survival of the industry lies in the control and improvement of the yield of integrated circuit chips. In the research of integrated circuit yield prediction model, some scholars have put forward a variety of yield models since the 1960s, and the early research mainly focused on finding the relationship between yield and on-line defects. As the process improves, the design becomes more difficult, and the yield prediction is expected to be more accurate. In this paper, we propose two models of yield loss. The first type of yield loss mode, the loss of yield caused by line defects. The second type of yield loss mode, chip process design defects caused by yield loss. We use the electrical test parameters as independent variables and use the statistical model to accurately predict the loss of yield. By establishing multivariate piecewise functions of two kinds of yield patterns, we try to reduce repeated information by principal component analysis (PCA), find suitable segmental points by using decision tree method, and establish Logistic regression models for segmented parts respectively. According to the results of model analysis, it is found that the yield prediction model improves the error greatly. This multivariate piecewise model also explains the coexistence of two yield loss models. Based on this method, a set of standard flow can be established for the construction of statistical model, and the standard can be automated by computer program. Easy to use this tool, timely detection of production anomalies, reduce losses.
【學(xué)位授予單位】：華東師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：O212.1

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