Modeling Hot Rolling Manufacturing Process Using Soft Computing Techniques
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- @Article{Faris2013a,
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author = "Hossam Faris and Alaa Sheta and Ertan Oznergiz",
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title = "Modeling Hot Rolling Manufacturing Process Using Soft
Computing Techniques",
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journal = "International Journal of Computer Integrated
Manufacturing",
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year = "2013",
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volume = "26",
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number = "8",
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pages = "762--771",
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keywords = "genetic algorithms, genetic programming, hot rolling
process, industrial process",
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publisher = "Taylor \& Francis",
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ISSN = "0951-192X",
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URL = "http://www.tandfonline.com/doi/pdf/10.1080/0951192X.2013.766937",
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DOI = "doi:10.1080/0951192X.2013.766937",
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size = "10 pages",
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abstract = "Steel making industry is becoming more competitive due
to the high demand. In order to protect the market
share, automation of the manufacturing industrial
process is vital and represents a challenge. Empirical
mathematical modelling of the process was used to
design mill equipment, ensure productivity and service
quality. This modelling approach shows many problems
associated to complexity and time consumption.
Evolutionary computing techniques show significant
modelling capabilities on handling complex non-linear
systems modelling. In this research, symbolic
regression modelling via genetic programming is used to
develop relatively simple mathematical models for the
hot rolling industrial non-linear process. Three models
are proposed for the rolling force, torque and slab
temperature. A set of simple mathematical functions
which represents the dynamical relationship between the
input and output of these models shall be presented.
Moreover, the performance of the symbolic regression
models is compared to the known empirical models for
the hot rolling system. A comparison with experimental
data collected from the Ere[gtilde]li Iron and Steel
Factory in Turkey is conducted for the verification of
the promising model performance. Genetic programming
shows better performance results compared to other soft
computing approaches, such as neural networks and fuzzy
logic.",
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notes = "http://www.tandfonline.com/action/journalInformation?show=aimsScope&journalCode=tcim20",
- }
Genetic Programming entries for
Hossam Faris
Alaa Sheta
Ertan Oznergiz
Citations