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NSF Young Investigator: Toward Neural Network Based Modeling, Control and Diagnosis of Semiconductor Manufacturing Processes

NSF Young Investigator: Toward Neural Network Based Modeling, Control and Diagnosis of Semiconductor Manufacturing Processes
NSF 青年研究员:面向半导体制造过程的基于神经网络的建模、控制和诊断
批准号:
9358163
负责人:
Gary May
金额:
$27.5万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
1993
资助国家:
美国
项目状态:
已结题
起止时间:
1993-08-15 至 2000-01-31

项目摘要

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中文摘要
翻译
9358163 5月这项研究涉及将计算机集成制造(IC-CIM)技术应用于生产高性能多芯片模块和其他集成电路所用的两个关键制造工艺:等离子体增强化学气相沉积(PECVD)和反应离子刻蚀(RIE)。在工艺序列中使用这些工艺来沉积和蚀刻二氧化硅介质层。计算机集成制造的几个方面成功地应用于其他蚀刻和沉积工艺。对于这些应用,传统的基于统计的过程建模、控制和诊断方法是实现IC-CIM目标的主要方法。然而,最近的研究表明,神经网络在过程建模方面提供了巨大的希望。事实上,神经过程模型已经被证明比它们的统计对应模型更准确和更健壮。这是因为这些网络具有高度的并行性和连通性,粗略地模仿了人类布莱恩的架构。预计神经网络的创新使用也将在过程监测、控制和设备诊断方面产生重大影响。该研究项目将研究和实现几种新的基于神经网络的方法,用于RIE和PECVD的监测、建模、控制和诊断。这些技术将专门应用于高性能多芯片模块程序,但开发的方法将是通用的,很容易适用于其他电子制造工艺和设备。
英文摘要
9358163 May The research involves applying implementation of computer- integrated manufacturing (IC-CIM) techniques to two critical fabrication processes used in the production of high performance multichip modules and other integrated circuits: plasma-enhanced chemical vapor deposition (PECVD) and reactive ion etching (RIE). These precesses are used in the process sequence to deposit and etch silicon dioxide dielectric layers. Several aspects of computer-integrated manufacturing successfully applied to other etching and deposition processes. For these applications, traditional statistically-based approaches to process modeling, control and diagnosis represent the predominant methods to achieve IC-CIM objectives. However, more recent efforts have shown that neural networks offer great promise in process modeling. In fact, neural process models have been shown to be both more accurate and more robust than their statistical counterparts. This is due to the high degree of parallelism and connectivity in these networks, which crudely mimics the architecture of the human brian. It is anticipated that the innovative use of neural networks will also have a significant impact in process monitoring, control, and equipment diagnosis as well. This program of research will investigate and implement several novel neural network based approaches to the monitoring, modeling, control, and diagnosis of RIE and PECVD. These techniques will be applied specifically to a high performance multichip module program, but the methodology developed will be generic and readily applicable to other electronics manufacturing processes and equipment.
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2012 Presidential Awards for Excellence in Science, Mathematics and Engineering Mentoring (PAESMEM) Awardee - Dr. Gary S. May (Individual Category)
  • 批准号:
    1201714
  • 项目类别:
    Standard Grant
  • 资助金额:
    $1.0万
  • 财政年份:
    2015
  • 负责人:
    Gary May
  • 依托单位:
IRES: Summer Undergraduate Research in Electrical and Computer Engineering and Computer Science in Metz, France (SURE International)
  • 批准号:
    0651835
  • 项目类别:
    Standard Grant
  • 资助金额:
    $14.97万
  • 财政年份:
    2007
  • 负责人:
    Gary May
  • 依托单位:
REU Site: SURE - Summer Undergraduate Research in Engineering
  • 批准号:
    0453295
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $0.0万
  • 财政年份:
    2005
  • 负责人:
    Gary May
  • 依托单位:
AGEP: FACES: Facilitating Academic Careers in Engineering and Science
  • 批准号:
    0450303
  • 项目类别:
    Cooperative Agreement
  • 资助金额:
    $784.69万
  • 财政年份:
    2004
  • 负责人:
    Gary May
  • 依托单位:
海外基金