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Artificial neural network modelling and optimization of elastic and an-elastic spring back in polymer parts produced through ISF

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Abstract

Traditional polymer processing techniques results in thermal degradation of the desired mechanical properties of a component. Incremental sheet forming (ISF), an innovative flexible cold forming process, can avoid this issue. However, this type of cold processing suffers from serious drawback of spring back due to elastic recovery. Therefore, process control is mandatory to achieve the desired part accuracy. This requires employment of a conducive set of process parameters, thereby turning this into an optimization problem. Using statistical techniques, though beneficial, does not result in an acceptable mean squared error (MSE). In this paper, we explore the use of machine learning methods for error prediction and parameter optimization. Particularly, we propose to use the combination of genetic algorithm and artificial neural network hybrid model for optimized set of parameters that result in a greedy minimized shape error. Experiments on Polypropylene sheet show that the proposed approach results in better optimization compared to statistical technique in minimizing the MSE.

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Included in the manuscript.

Code availability

Matlab built-in GA and ANN toolboxes.

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Funding

Naila Rahman wishes to thank the Ghulam Ishaq Khan Institute of Engineering Sciences and Technology for supporting her MS research via a fully funded scholarship under its GA scheme.

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Authors and Affiliations

  1. Machine Learning and Data Science (MDS) Lab, G.I.K Institute, Topi, Pakistan

    Syed Fawad Hussain & Naila Rahman

  2. Faculty of Computer Science and Engineering, G.I.K. Institute, Topi, 23460, Pakistan

    Syed Fawad Hussain & Naila Rahman

  3. Faculty of Mechanical Engineering, G.I.K Institute, Topi, 23460, Pakistan

    Ghulam Hussain

Authors
  1. Syed Fawad Hussain
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  2. Ghulam Hussain
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Correspondence to Syed Fawad Hussain.

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Hussain, S.F., Hussain, G. & Rahman, N. Artificial neural network modelling and optimization of elastic and an-elastic spring back in polymer parts produced through ISF. Int J Adv Manuf Technol 118, 2163–2176 (2022). https://doi.org/10.1007/s00170-021-08054-7

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  • DOI: https://doi.org/10.1007/s00170-021-08054-7

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