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Neural network model of the profile of hot-rolled strip

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Abstract

The dynamics of shape or profile depends on the several process parameters in a hot strip mill. This research paper presents the prediction of the profile or strip crown generated during rolling in the finishing stands of a hot strip mill with the use of artificial neural network (ANN) by taking into account the operational parameters such as width, thickness, speed, and roll bending, among others. A multi-layer perceptron neural network is trained with a back-propagation algorithm. Verification of the model is made by a comparison of the measured and predicted strip profile. A sensitivity analysis of the contributing factors to the profile variations is also carried out that shows the strip speed as one of the major contributor to the strip profile. A good comparison is found between the measured strip crown with the ANN-predicted crown demonstrating the modeling route as a robust one.

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Authors and Affiliations

  1. R & D Division, Tata Steel, Jamshedpur, 831007, India

    Sudipta Sikdar

  2. Allgemein Engineering Bureau Pvt. Ltd., Jamshedpur, 831001, India

    Sabita Kumari

Authors
  1. Sudipta Sikdar
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  2. Sabita Kumari
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Correspondence to Sudipta Sikdar.

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Sikdar, S., Kumari, S. Neural network model of the profile of hot-rolled strip. Int J Adv Manuf Technol 42, 450–462 (2009). https://doi.org/10.1007/s00170-008-1623-1

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  • DOI: https://doi.org/10.1007/s00170-008-1623-1

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