PECASE: A Unified Methodology for Variation Management and Reduction in Multistage Manufacturing Processes

PECASE:多阶段制造流程中的变异管理和减少的统一方法

基本信息

  • 批准号:
    0133942
  • 负责人:
  • 金额:
    $ 37.5万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2002
  • 资助国家:
    美国
  • 起止时间:
    2002-07-01 至 2005-10-31
  • 项目状态:
    已结题

项目摘要

Proposal Title: PECASE: A Unified Methodology for Variation Management and Reduction in Multistage Manufacturing ProcessesInstitution: University of ArizonaThis PECASE grant sponsors research and teaching efforts in developing a unified methodology for variation management and reduction in Multistage Manufacturing Processes (MMPs). A MMP generally involves multiple operations to produce a product, which can be found in many industrial processes such as automotive body assembly, machining lines, progressive stamping, and semiconductor manufacturing. In a MMP, each operation adds inherent design variation when no fault occurs, and special assignable variation when a fault occurs, to the workpiece variation. The output workpiece of one operation is the input of the next operation. The final product variation is an accumulation of variation from all operations. Therefore, the characteristics of variation propagation is very complex in MMPs, depending on both product and process design. The research efforts in the project will develop methodologies to achieve on-target production with minimum variance by addressing both design and manufacturing concurrently. The research focus is to develop: (a) a math-based model to describe the variation propagation in a MMP; (b) an integrated methodology for variation management through design synthesis and optimization; and (c) statistical methods driven by engineering models for quick root cause identification and product defect prevention. In addition to research, new curriculums and courses will be developed. Various collaborative efforts with industry, international universities, and K-12 schools will be conducted in research and education in the project.If successful, the project results will enrich the science base and technologies in variation reduction and process control methodologies for MMPs, which include: (a) analytical (rather than empirical) modeling of MMP variation and its propagation; (b) synthesis (rather than analysis) of product/process tolerance for optimal management of inherent design variation to minimize their impact on final products; (c) real-time root-cause identification (rather than change detection) for manufacturing process control and continuous improvement; and (d) prognostics (rather than defect inspection) for defect prevention throughout the manufacturing lifetime. The developed unified methodology will generate significant economic impacts in industrial sectors where MMPs are used.This project was originally funded as a CAREER award, and was converted to a Presidential Early Career Award for Engineers and Scientists (PECASE) award in May 2004.
提案名称:PECASE:多阶段制造过程中差异管理和减少的统一方法机构:亚利桑那大学该PECASE资助研究和教学工作,以开发多阶段制造过程(MMPs)中差异管理和减少的统一方法。MMP通常涉及生产产品的多个操作,可以在许多工业过程中找到,例如汽车车身组装,加工线,级进冲压和半导体制造。在MMP中,当没有发生故障时,每个操作都增加了固有的设计变化,当发生故障时,每个操作都增加了工件变化的可分配变化。一个操作的输出工件是下一个操作的输入。最终产品的变化是所有操作变化的累积。因此,在MMPs中,变异传播的特征非常复杂,这取决于产品和工艺设计。该项目的研究工作将开发方法,通过同时解决设计和制造问题,以最小的方差实现目标生产。研究的重点是:(a)建立一个基于数学的模型来描述MMP中的变异传播;(b)通过设计综合和优化来管理变化的综合方法;(c)由工程模型驱动的统计方法,用于快速识别根本原因和产品缺陷预防。除了研究之外,还将开发新的课程和课程。该项目将与工业界、国际大学和K-12学校在研究和教育方面进行各种合作。如果成功,项目成果将丰富MMP变异减少和过程控制方法的科学基础和技术,其中包括:(a) MMP变异及其传播的分析(而不是经验)建模;(b)综合(而不是分析)产品/工艺公差,以对固有设计变化进行最佳管理,以尽量减少其对最终产品的影响;(c)用于生产过程控制和持续改进的实时根本原因识别(而不是变更检测);(d)在整个制造生命周期内进行缺陷预防的预测(而不是缺陷检查)。开发的统一方法将对使用MMPs的工业部门产生重大的经济影响。该项目最初是作为职业奖资助的,并于2004年5月转换为工程师和科学家的总统早期职业奖(PECASE)奖。

项目成果

期刊论文数量(0)
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会议论文数量(0)
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Jionghua (Judy) Jin其他文献

Statistical prediction of eye locations for drivers of military ground vehicles
  • DOI:
    10.1016/j.ergon.2017.03.007
  • 发表时间:
    2017-05-01
  • 期刊:
  • 影响因子:
  • 作者:
    Yaser Zerehsaz;Jionghua (Judy) Jin;Sheila M. Ebert;Matthew P. Reed
  • 通讯作者:
    Matthew P. Reed
Sample size calculations for a functional human motion analysis: Application to vehicle ingress discomfort prediction
  • DOI:
    10.1016/j.ergon.2018.09.010
  • 发表时间:
    2019-01-01
  • 期刊:
  • 影响因子:
  • 作者:
    Hadi Ibrahim Masoud;Matthew P. Reed;Jionghua (Judy) Jin
  • 通讯作者:
    Jionghua (Judy) Jin

Jionghua (Judy) Jin的其他文献

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{{ truncateString('Jionghua (Judy) Jin', 18)}}的其他基金

Modeling and Inferring of Multichannel Sensing Data in Complex Manufacturing Procsses
复杂制造过程中多通道传感数据的建模和推断
  • 批准号:
    1233108
  • 财政年份:
    2012
  • 资助金额:
    $ 37.5万
  • 项目类别:
    Standard Grant
PECASE: A Unified Methodology for Variation Management and Reduction in Multistage Manufacturing Processes
PECASE:多阶段制造流程中的变异管理和减少的统一方法
  • 批准号:
    0549306
  • 财政年份:
    2005
  • 资助金额:
    $ 37.5万
  • 项目类别:
    Standard Grant
Engineering-Driven Wavelet Analysis of Cyclic Functional Data for Multiple Embedded Operations Diagnosis
用于多嵌入式操作诊断的循环函数数据的工程驱动小波分析
  • 批准号:
    0541750
  • 财政年份:
    2005
  • 资助金额:
    $ 37.5万
  • 项目类别:
    Standard Grant
Engineering-Driven Wavelet Analysis of Cyclic Functional Data for Multiple Embedded Operations Diagnosis
用于多嵌入式操作诊断的循环函数数据的工程驱动小波分析
  • 批准号:
    0500176
  • 财政年份:
    2005
  • 资助金额:
    $ 37.5万
  • 项目类别:
    Standard Grant

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