课题基金 / 基金详情

Cutting Tool Wear and Performance Estimation using Acoustic Emission

Cutting Tool Wear and Performance Estimation using Acoustic Emission
使用声发射进行切削刀具磨损和性能评估
批准号:
511847-2017
负责人:
Mechefske, Christopher
金额:
$1.82万
依托单位:
依托单位国家:
加拿大
项目类别:
Engage Grants Program
财政年份:
2017
资助国家:
加拿大
项目状态:
已结题
起止时间:
2017-01-01 至 2018-12-31

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中文摘要
翻译
为了保持商业竞争力,扩大产品和服务范围,Checkfluid公司不断寻求优化生产效率、最大化产品质量和开发新服务的方法。本课题的重点是开发机床操作完整性和零件质量的在线精确测量方法。成功将导致操作员的实时反馈,这将有助于提高制造效率,并消除人工零件质量检查的需要。这两项成果都将显著提高Checkfluid的盈利能力。这个项目的目标是双重的。首先是组装基于加工过程的精确物理模型。第二是开发准确的混合数据/基于物理的分析,显示出在不同机器健康状态和零件质量之间提供明确区分的潜力。结合这些目标将形成一套经过实验验证的数据分析程序,以优化制造机器的使用和可靠的产品质量。
英文摘要
In order to remain commercially competitive and extend product and service offerings Checkfluid Ltd.continually searches for ways to optimize production efficiency, maximize product quality and develop newservices. The focus of this project is the development of online methods to accurately measure machine tooloperational integrity and part quality. Success will result in real-time operator feedback that will facilitateimproved manufacturing efficiency and eliminate the need for manual part quality inspections. Both of theseoutcomes will significantly improve Checkfluid's profitability.The objectives of this project are two-fold. The first will be to assemble accurate physics based models of themachining process. The second will be to develop accurate hybrid data/physics based analytics that showpotential to provide a clear distinction between different machine health states and part quality. Combinedthese objectives will form a set of experimentally verified data analysis procedures that allow optimized use ofmanufacturing machines and reliable product quality.
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Hybrid Data-driven Physics-based Modeling for Machine Fault Detection, Diagnosis, and Prediction
  • 批准号:
    RGPIN-2019-03967
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.84万
  • 财政年份:
    2022
  • 负责人:
    Mechefske, Christopher
  • 依托单位:
Fuselage structural dynamic and vibro-acoustic analysis, modeling, and optimization
  • 批准号:
    536637-2018
  • 项目类别:
    Collaborative Research and Development Grants
  • 资助金额:
    $3.1万
  • 财政年份:
    2021
  • 负责人:
    Mechefske, Christopher
  • 依托单位:
Hybrid Data-driven Physics-based Modeling for Machine Fault Detection, Diagnosis, and Prediction
  • 批准号:
    RGPIN-2019-03967
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.84万
  • 财政年份:
    2021
  • 负责人:
    Mechefske, Christopher
  • 依托单位:
Machine tool monitoring using data analytics and physics-based models
  • 批准号:
    523509-2018
  • 项目类别:
    Collaborative Research and Development Grants
  • 资助金额:
    $2.33万
  • 财政年份:
    2021
  • 负责人:
    Mechefske, Christopher
  • 依托单位:
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