Corrosion Science and Technology

  • 제23권3호
  • /
  • Pages.228-234
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  • 2024
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  • 1598-6462(pISSN)
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  • 2288-6524(eISSN)
한국부식방식학회 (The Corrosion Science Society of Korea)
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Artificial Intelligence-Based Descriptive, Predictive, and Prescriptive Coating Weight Control Model for Continuous Galvanizing Line

  • 투고 : 2024.02.07
  • 심사 : 2024.05.13
  • 발행 : 2024.06.30
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초록

Zinc wiping is a phenomenon used to control zinc-coating thickness on steel substrate during hot dip galvanizing by equipment called air knife. Uniformity of zinc coating weight in length and width profile along with surface quality are most critical quality parameters of galvanized steel. Deviation from tolerance level of coating thickness causes issues like overcoating (excess consumption of costly zinc) or undercoating leading to rejections due to non-compliance of customer requirement. Main contributor of deviation from target coating weight is dynamic change in air knives equipment setup when thickness, width, and type of substrate changes. Additionally, cold coating measurement gauge measure coating weight after solidification but are installed down the line from air knife resulting in delayed feedback. This study presents a coating weight control model (Galvantage) predicting critical air knife parameters air pressure, knife distance from strip and line speed for coating control. A reverse engineering approach is adopted to design a predictive, prescriptive, and descriptive model recommending air knife setups that estimate air knife distance and expected coating weight in real time. Implementation of this model eliminates feedback lag experienced due to location of coating gauge and achieving setup without trial-error by operator.

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참고문헌

  1. A. R. Marder, The metallurgy of zinc-coated steel, Progress in materials science, 45, 191 (2000). Doi: http://dx.doi.org/10.1016/S0079-6425(98)00006-1
  2. L. Chen, R. Fourmentin, and J. R. Mc Dermid, Morphology and kinetics of interfacial layer formation during continuous hot-dip galvanizing and galvannealing, Metallurgical and materials Transactions A, 39, 2128 (2008). Doi: https://doi.org/10.1007/s11661-008-9552-z
  3. J. A. Thornton, and H. F. Graff, An analytical description of the jet finishing process for hot-dip metallic coatings on strip, Metallurgical Transactions B, 7, 607 (1976). Doi: https://doi.org/10.1007/BF02698594
  4. H. Ellen and C. V. Tu, An analysis of jet stripping of liquid coatings, Journal of Fluids Engineering-Transactions of the ASME, 106, 399 (1984). Doi: https://doi.org/10.1115/1.3243137
  5. C. V. Tu, and D. H. Wood, Wall pressure and shear stress measurements beneath an impinging jet, Experimental thermal and fluid science, 13, 364 (1996). Doi: https://doi.org/10.1016/S0894-1777(96)00093-3
  6. E. A. Elsaadawy, G. S. Hanumanth, A. K. S. Balthazaar, J. R. McDermid, A. N. Hrymak, and J. F. Forbes, Coating weight model for the continuous hot-dip galvanizing process, Metallurgical and Materials Transactions B, 38, 413 (2007). Doi: https://doi.org/10.1007/s11663-007-9037-2
  7. K. Myrillas, A. Gosset, P. Rambaud, M. Anderhuber, J. M. Mataigne, and J. M. Buchlin, Technique for delaying splashing in jet wiping process, Chemical Engineering and Processing: Process Intensification, 50, 466 (2011). Doi: https://doi.org/10.1016/j.cep.2010.09.011
  8. Y. Zhang, Q. P. Cui, F. Q. Shao, J. S. Wang, and H. Y. Zhao, Influence of air-knife wiping on coating thickness in hot-dip galvanizing, Journal of Iron and Steel Research International, 19, 70 (2012). Doi: https://doi.org/10.1016/S1006-706X(12)60130-7