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Computational Techniques for Mapping Design Features to Machining Features: Machining Algebra and Dimensioning and Tolerancing Mapping

Computational Techniques for Mapping Design Features to Machining Features: Machining Algebra and Dimensioning and Tolerancing Mapping
将设计特征映射到加工特征的计算技术:加工代数以及尺寸和公差映射
批准号:
9522971
负责人:
Jami Shah
金额:
$25.15万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
1995
资助国家:
美国
项目状态:
已结题
起止时间:
1995-10-01 至 1999-03-31

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中文摘要
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英文摘要
9522971 Shah This project investigates several computational techniques for transferring product geometry data from design to manufacturing without human intervention. The project is divided into two parts. The first component of the project is the development of machining algebra for geometric representation of tool-workpiece interaction for all machining processes. This provides the mathematical basis for determining the machining process that produces each machining feature on a given part. The second component of the project is a computational model for mapping dimensions and tolerances (D&T) while preserving the design intent. The key elements of the model are geometric building blocks, directed geometric constraints, and degree of freedom analysis for validation. Methods for redistributing the designers D&T between machining features will also be developed. This project addresses a critical area of industry need, viz., design and manufacturing integration. The lack of this integration results in longer development times because manufacturing planning today is a very labor-intensive activity. The machining algebra has the potential to capture the fundamental characteristics of common machining processes, replacing shallow heuristic rules used now, enhancing the degree to which manufacturing can be automated. The methods proposed are generic; they are independent of particular computer aided design (CAD) or computer aided process planning (CAPP) systems used. Each of the computational methods can be used independent of each other, making it attractive to incorporate them into existing CAD/CAPP systems. This will enhance the communication between design and manufacturing and enhance process planning productivity, thus reducing time to market.
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GOALI/Collaborative Research: Curating Complex Data Sets for Machine Learning Applied to Flexible Assembly Design and Optimization
  • 批准号:
    2029905
  • 项目类别:
    Standard Grant
  • 资助金额:
    $33.34万
  • 财政年份:
    2021
  • 负责人:
    Jami Shah
  • 依托单位:
EAGER: MyDesignSpace: Discovering Design Patterns from Holistic Ideation Web Tool
  • 批准号:
    1150271
  • 项目类别:
    Standard Grant
  • 资助金额:
    $5.0万
  • 财政年份:
    2011
  • 负责人:
    Jami Shah
  • 依托单位:
Major: Understanding and Aiding Problem Formulation in Creative Conceptual Design
  • 批准号:
    1002910
  • 项目类别:
    Standard Grant
  • 资助金额:
    $74.1万
  • 财政年份:
    2010
  • 负责人:
    Jami Shah
  • 依托单位:
EAGER: Holistic Ideation for Creative Design
  • 批准号:
    1045644
  • 项目类别:
    Standard Grant
  • 资助金额:
    $7.47万
  • 财政年份:
    2010
  • 负责人:
    Jami Shah
  • 依托单位:
国内基金
海外基金
EstimatingLarge Demand Systems with MachineLearning Techniques
  • 批准号:
    --
  • 项目类别:
    外国学者研究基金
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    IoshuaAlex
  • 依托单位: