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Prediction of Tool Wear Rate and Pattern during Metal Cutting

Prediction of Tool Wear Rate and Pattern during Metal Cutting
金属切削过程中刀具磨损率和模式的预测
批准号:
RGPIN-2014-06223
负责人:
Ng, EuGene
金额:
$1.75万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2014
资助国家:
加拿大
项目状态:
已结题
起止时间:
2014-01-01 至 2015-12-31

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中文摘要
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英文摘要
Tool wear rate is highly dependent on factors like contact pressure, interface contact velocity, temperature, material properties and surface roughness. Over the last half century, limited tool wear models were developed to predict tool life, tool wear rate and pattern during metal cutting. Accurate and important knowledge on predicting the effect of tool microstructure on tool wear rate and tool wear pattern during metal cutting will enable researchers and engineers to optimize machining parameters for high value components, leading to enhanced part quality as well as reducing part distortion and minimizing post machining processes. Unfortunately very few research publications to investigate the effect of tool material microstructure on tool wear rate and wear pattern models are found. The long term objective of this research is to develop numerical models to predict tool wear rate and pattern during metal cutting. This research will develop a semi numerical and empirical approach to determine the coefficient of friction and experimentally investigate the effect of surface roughness on the coefficient of friction. A unique tribological test configuration will be designed to determine the coefficient of friction under high contact stress and at elevated temperature. To create such contact conditions that are similar in metal cutting, the orthogonal cutting configuration will be modified. A finite element (FE) model will be used to predict the normal contact pressure and interface temperature. Following on from here, an unique methodology will be developed to calibrate tool wear model constants with limited or few experimental parameters. The calibration constants will be a function of tool carbide particle size, which is a unique aspect of this research. An orthogonal cutting FE model will be developed to model the effects of tool microstructure and the worn geometry and shape of the cutting edge on normal contacting stress, interface sliding velocity, and along the interface contacting temperature. The orthogonal cutting model will initially employ the Arbitrary Lagrangian and Eulerian (ALE) formulation technique to simulate the transient cutting process. Once the model reaches steady state, the model will then switch from ALE to Eulerian formulation by controlling the remeshing boundary conditions. This approach will significantly reducing computational time. This will reduce calibration time and improve tool wear rate prediction. Lastly, this research will develop a physics-based approach to simulate tool wear pattern and rate of wear during orthogonal cutting using the FE method only. In order to simulate wear rate and pattern, an erosion subroutine must be incorporated into the tool wear model. The erosion subroutine will comprise an erosion criterion and an element deletion scheme. The erosion criterion will be a function of hydrostatic pressure, Von Mises stress and temperature. The element deletion scheme will be activated when the erosion criterion has been met. This scheme will remove the element from the tool's body, generate a new tool surface geometry, and transfer the loading and boundary conditions to this new surface. Extensive experiments will be performed to validate the models. This research will contribute to raise the visibility of Canadian effort in physics based tool wear pattern modelling. The expected research outcomes will establish Canada as one of the top research countries on using FE method to model the effect of tool microstructure on tool wear pattern and tool wear rate
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Prediction of Tool Wear Rate and Pattern during Metal Cutting
  • 批准号:
    RGPIN-2014-06223
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.75万
  • 财政年份:
    2018
  • 负责人:
    Ng, EuGene
  • 依托单位:
Additive Manufacturing of Selected Automotive Components
  • 批准号:
    513513-2017
  • 项目类别:
    Engage Grants Program
  • 资助金额:
    $1.82万
  • 财政年份:
    2017
  • 负责人:
    Ng, EuGene
  • 依托单位:
Prediction of Tool Wear Rate and Pattern during Metal Cutting
  • 批准号:
    RGPIN-2014-06223
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.75万
  • 财政年份:
    2017
  • 负责人:
    Ng, EuGene
  • 依托单位:
Prediction of Tool Wear Rate and Pattern during Metal Cutting
  • 批准号:
    RGPIN-2014-06223
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.75万
  • 财政年份:
    2016
  • 负责人:
    Ng, EuGene
  • 依托单位:
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