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Prediction model for determining the optimum operational parameters in laser forming of fiber-reinforced composites

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Abstract

Composite materials are widely employed in various industries, such as aerospace, automobile, and sports equipment, owing to their lightweight and strong structure in comparison with conventional materials. Laser material processing is a rapid technique for performing the various processes on composite materials. In particular, laser forming is a flexible and reliable approach for shaping fiber-metal laminates (FMLs), which are widely used in the aerospace industry due to several advantages, such as high strength and light weight. In this study, a prediction model was developed for determining the optimal laser parameters (power and speed) when forming FML composites. Artificial neural networks (ANNs) were applied to estimate the process outputs (temperature and bending angle) as a result of the modeling process. For this purpose, several ANN models were developed using various strategies. Finally, the achieved results demonstrated the advantage of the models for predicting the optimal operational parameters.

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Authors and Affiliations

  1. Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, Via Eudossiana 18, 00184, Rome, Italy

    Annamaria Gisario & Atabak Rahimzadeh

  2. Department of Mechanical and Industrial Engineering, The University of Roma Tre, Via Vito Volterra 62, 00146, Rome, Italy

    Mehrshad Mehrpouya & Massimiliano Barletta

  3. Department of Mechanical Engineering, University of Bath, Bath, BA2 7AY, UK

    Andrea De Bartolomeis

Authors
  1. Annamaria Gisario
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  2. Mehrshad Mehrpouya
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  3. Atabak Rahimzadeh
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  4. Andrea De Bartolomeis
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  5. Massimiliano Barletta
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Correspondence to Mehrshad Mehrpouya.

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Gisario, A., Mehrpouya, M., Rahimzadeh, A. et al. Prediction model for determining the optimum operational parameters in laser forming of fiber-reinforced composites. Adv. Manuf. 8, 242–251 (2020). https://doi.org/10.1007/s40436-020-00304-3

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  • DOI: https://doi.org/10.1007/s40436-020-00304-3

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