Genetic equation for the prediction of tool-chip contact length in orthogonal cutting
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- @Article{Zadshakoyan:2013:EAAI,
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author = "M. Zadshakoyan and V. Pourmostaghimi",
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title = "Genetic equation for the prediction of tool-chip
contact length in orthogonal cutting",
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journal = "Engineering Applications of Artificial Intelligence",
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volume = "26",
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number = "7",
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pages = "1725--1730",
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year = "2013",
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month = aug,
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keywords = "genetic algorithms, genetic programming, Cutting
parameters, Machining, Tool-chip contact length",
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ISSN = "0952-1976",
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DOI = "doi:10.1016/j.engappai.2012.10.016",
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URL = "http://www.sciencedirect.com/science/article/pii/S0952197612002850",
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abstract = "In metal cutting, it has been acknowledged that the
tool-chip contact length significantly affects many
aspects of machining such as chip formation, cutting
forces, cutting temperatures, tool wear and tool life.
Important decrease in the tool-chip contact length,
decreases the thickness of the secondary shear zone,
which leads to a decrease of the cutting temperature
and cutting force. As a result, it has a great effect
on finish surface and tool life. Several ways have been
proposed in different works to find its value, which
have given discordant results for the same set of
cutting conditions. In this paper, the genetic equation
for the tool-chip contact length is developed with the
use of the experimentally measured contact length
values and genetic programming. The suggested equation
has shown to correspond well with experimental data in
various machining conditions with associated cutting
parameters and this model predicts tool-chip contact
length better than other known solutions.",
- }
Genetic Programming entries for
Mohammad Zadshakoyan
Vahid Pourmostaghimi
Citations