Roll wear modeling using genetic programming -- industry case study
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- @Article{Kovacic:2019:MTAEC9,
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author = "Miha Kovacic and Andrej Mihevc and Milan Tercelj",
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title = "Roll wear modeling using genetic programming --
industry case study",
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journal = "Materials and Technology",
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journal_si = "Materiali in Tehnologije",
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year = "2019",
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volume = "53",
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number = "3",
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pages = "319--325",
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keywords = "genetic algorithms, genetic programming, roll wear,
hot rolling, prediction, linear regression",
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ISSN = "1580-2949",
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URL = "http://mit.imt.si/Revija/izvodi/mit193/kovacic.pdf",
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URL = "http://mit.imt.si/mit193.html",
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DOI = "doi:10.17222/mit.2018.104",
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size = "7 pages",
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abstract = "Store Steel Ltd. is one of the largest flat spring
steel producers in Europe. Using the continuous rolling
line (10 stands: 6 horizontal, 4 vertical), all the
rolled dimensions, including round (more than 80
nominal diameters), flat (more than 650 shapes and
dimensions) and square bars (13 different sizes), can
be rolled each month. The purpose of the research was
to identify the parameters affecting the working roll
wear in the hot-rolling process. For this purpose, we
collected data during the 2013 annual production on the
first stand of the continuous roll mill for rolling of
diameters from f20mm to f58mm for which data of the
groove shape and surface, roll diameter, contact time,
carbon equivalent, rolling temperature and quantity of
the rolled material are available. After roll wear-out
they are machined using a turning operation. The root
cause why the rolls were machined was not collected. To
evaluate the roll wear-out, the quantity of rolled
material before the machining of rolls was used.
Prediction of the quantity of rolled material before
the machining of rolls was conducted using linear
regression and genetic programming. The developed
models were validated using the data from 2014. The
validation showed that in the case of excluding the
fatigue cracks from collected data the prediction could
be improved drastically. The results of the research
can be used in practice for predicting roll wear and
consequently roll maintenance on the basis of rolling
schedule quantities.",
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notes = "In English.
UDK 004.414.23:620.193.95:62-222
Modeliranje obrabe valjev z genetskim programiranjem,
primer iz industrije
MTAEC9",
- }
Genetic Programming entries for
Miha Kovacic
Andrej Mihevc
Milan Tercelj
Citations