Technological Parameter Optimization of Disc-Milling Grooving of Titanium Alloy Based on Grey Correlation Degree
In present paper, aim to some problems such as big material removal rate, serious tool wear and obvious plastic deformation during disc-milling grooving, the orthogonal experiment with three factors and three levels was designed. First, the multi-objective optimization was converted to single-object...
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The Northwestern Polytechnical University
2018-02-01
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doaj-1e1d5eae583643cdad125efa3643ff532021-05-03T01:30:51ZzhoThe Northwestern Polytechnical UniversityXibei Gongye Daxue Xuebao1000-27582018-02-0136113914810.1051/jnwpu/20183610jnwpu2018361p139Technological Parameter Optimization of Disc-Milling Grooving of Titanium Alloy Based on Grey Correlation DegreeIn present paper, aim to some problems such as big material removal rate, serious tool wear and obvious plastic deformation during disc-milling grooving, the orthogonal experiment with three factors and three levels was designed. First, the multi-objective optimization was converted to single-objective optimization based on grey correlation analysis, the influence weight of material removal rate, tool life and the depth of residual stress layer on grey correlation degree was determined via principal component analysis. Second, by means of regression analysis of experiment data, the prediction model of grey correlation degree and technological parameters was developed. Accordingly, the variation of material removal rate, tool life, the depth of residual stress layer and grey correlation degree resulted from the various technological parameter were studied. Further, the optimization scheme of technological parameter was put forward. Finally, the technological parameters were optimized with response surface methodology. And then, the disc-milling grooving experiment was carried out. The experiment results showed that material removal rate can be improved significantly under the condition of meeting the request of tool life and the depth of residual stress layer.https://www.jnwpu.org/articles/jnwpu/pdf/2018/01/jnwpu2018361p139.pdfdisc-milling groovinggrey correlation degreeparameter optimizationmaterial removal ratetool lifedesign of experimentsmultiobjective optimization |
collection |
DOAJ |
language |
zho |
format |
Article |
sources |
DOAJ |
title |
Technological Parameter Optimization of Disc-Milling Grooving of Titanium Alloy Based on Grey Correlation Degree |
spellingShingle |
Technological Parameter Optimization of Disc-Milling Grooving of Titanium Alloy Based on Grey Correlation Degree Xibei Gongye Daxue Xuebao disc-milling grooving grey correlation degree parameter optimization material removal rate tool life design of experiments multiobjective optimization |
title_short |
Technological Parameter Optimization of Disc-Milling Grooving of Titanium Alloy Based on Grey Correlation Degree |
title_full |
Technological Parameter Optimization of Disc-Milling Grooving of Titanium Alloy Based on Grey Correlation Degree |
title_fullStr |
Technological Parameter Optimization of Disc-Milling Grooving of Titanium Alloy Based on Grey Correlation Degree |
title_full_unstemmed |
Technological Parameter Optimization of Disc-Milling Grooving of Titanium Alloy Based on Grey Correlation Degree |
title_sort |
technological parameter optimization of disc-milling grooving of titanium alloy based on grey correlation degree |
publisher |
The Northwestern Polytechnical University |
series |
Xibei Gongye Daxue Xuebao |
issn |
1000-2758 |
publishDate |
2018-02-01 |
description |
In present paper, aim to some problems such as big material removal rate, serious tool wear and obvious plastic deformation during disc-milling grooving, the orthogonal experiment with three factors and three levels was designed. First, the multi-objective optimization was converted to single-objective optimization based on grey correlation analysis, the influence weight of material removal rate, tool life and the depth of residual stress layer on grey correlation degree was determined via principal component analysis. Second, by means of regression analysis of experiment data, the prediction model of grey correlation degree and technological parameters was developed. Accordingly, the variation of material removal rate, tool life, the depth of residual stress layer and grey correlation degree resulted from the various technological parameter were studied. Further, the optimization scheme of technological parameter was put forward. Finally, the technological parameters were optimized with response surface methodology. And then, the disc-milling grooving experiment was carried out. The experiment results showed that material removal rate can be improved significantly under the condition of meeting the request of tool life and the depth of residual stress layer. |
topic |
disc-milling grooving grey correlation degree parameter optimization material removal rate tool life design of experiments multiobjective optimization |
url |
https://www.jnwpu.org/articles/jnwpu/pdf/2018/01/jnwpu2018361p139.pdf |
_version_ |
1721485913489408000 |