Metaheuristics in Manufacturing: Predictive Modeling of Tool Wear in Machining Using Genetic Programming
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- @InCollection{Zadshakoyan:2018:aamc,
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author = "Mohammad Zadshakoyan and Vahid Pourmostaghimi",
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title = "Metaheuristics in Manufacturing: Predictive Modeling
of Tool Wear in Machining Using Genetic Programming",
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booktitle = "Advancements in Applied Metaheuristic Computing",
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publisher = "IGI Global",
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year = "2018",
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editor = "Nilanjan Dey",
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chapter = "5",
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pages = "118--142",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "9781522541516",
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URL = "https://www.igi-global.com/chapter/metaheuristics-in-manufacturing/192002",
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DOI = "doi:10.4018/978-1-5225-4151-6.ch005",
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abstract = "The state of a cutting tool is an important factor in
any metal cutting process as additional costs in terms
of scrapped components, machine tool breakage and
unscheduled downtime result from worn tool usage.
Therefore, tool wear prediction plays an important role
in industry automation for higher productivity and
acceptable product quality. Therefore, in order to
increase the productivity of turning process, various
researches have been made recently for tool wear
estimation and classification in turning process. Chip
form is one of the most important factors commonly
considered in evaluating the performance of machining
process. On account of the effect of the progressive
tool wear on the shape and geometrical features of
produced chip, it is possible to predict some
measurable machining outputs such as crater wear.
According to experimentally performed researches,
cutting speed and cutting time are two extremely
effective parameters which contribute to the
development of the crater wear on the tool rake face.
As a result, these parameters will change the chip
radius and geometry. This chapter presents the
development of the genetic equation for the tool wear
using occurred changes in chip radius in turning
process. The development of the equation combines
different methods and technologies like evolutionary
methods, manufacturing technology, measuring and
control technology with the adequate hardware and
software support. The results obtained from genetic
equation and experiments showed that obtained genetic
equations are correlated well with the experimental
data. Furthermore, it can be used for tool wear
estimation during cutting process and because of its
parametric form, genetic equation enables us to analyse
the effect of input parameters on the crater wear
parameters.",
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notes = "University of Tabriz, Iran
https://www.igi-global.com/book/advancements-applied-metaheuristic-computing/182886",
- }
Genetic Programming entries for
Mohammad Zadshakoyan
Vahid Pourmostaghimi
Citations