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Deep Learning Based Baynat Foam Classification for Headliners Manufacturing

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17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022) (SOCO 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 531))

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Abstract

This paper shows the performance of four deep learning algorithms on Baynat foam classification (Resnet, Mobilenet, Inception and Xception). One of the key components on headliner manufacturing is the foam. It provides acoustic isolation, lightness and robustness. Together with foam, other components are added such as textile fabrics and fiber components. Depending on the foam cell-size distribution, right amount of glue to be applied is determined correspondingly. This paper introduce AI algorithms on foam classification. The experiments are carried out using a dataset of 3000 images of foam cuts obtained from a single foam block.

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Author information

Authors and Affiliations

  1. Department of Advanced Manufacturing 4.0, Grupo Antolín, Burgos, Spain

    Revanth Shankar Muthuselvam, Ramón Moreno, Mario Guemes & Miguel Del Río Cristobal

  2. University of Comillas, Cátedra de Industria Conectada, ICAI, Madrid, Spain

    Ignacio de Rodrigo Tobías & Alvaro Jesús López López

Authors
  1. Revanth Shankar Muthuselvam
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  2. Ramón Moreno
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  3. Mario Guemes
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  4. Miguel Del Río Cristobal
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  5. Ignacio de Rodrigo Tobías
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  6. Alvaro Jesús López López
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Corresponding author

Correspondence to Ramón Moreno .

Editor information

Editors and Affiliations

  1. Faculty of Engineering, University of Deusto, Bilbao, Spain

    Pablo García Bringas

  2. University of León, León, Spain

    Hilde Pérez García

  3. Mechanical Engineering Department, University of La Rioja, Logroño, La Rioja, Spain

    Francisco Javier Martinez-de-Pison

  4. Inteligencia Artificial, University of Oviedo, A Coruña, La Coruña, Spain

    José Ramón Villar Flecha

  5. Data Science and Big Data Lab, Pablo de Olavide University, Sevilla, Spain

    Alicia Troncoso Lora

  6. University of Oviedo, Oviedo, Spain

    Enrique A. de la Cal

  7. Department of Civil Engineering, University of Burgos, Burgos, Spain

    Álvaro Herrero

  8. School of engineering, Pablo Olavide University, Seville, Spain

    Francisco Martínez Álvarez

  9. DIGIP, University of Bergamo, Dalmine, Bergamo, Italy

    Giuseppe Psaila

  10. Department of Industrial Engineering, University of A Coruña, Ferrol, Spain

    Héctor Quintián

  11. Department of Computing Science, University of Salamanca, Salamanca, Spain

    Emilio S. Corchado Rodriguez

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Muthuselvam, R.S., Moreno, R., Guemes, M., Del Río Cristobal, M., de Rodrigo Tobías, I., López, A.J.L. (2023). Deep Learning Based Baynat Foam Classification for Headliners Manufacturing. In: García Bringas, P., et al. 17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022). SOCO 2022. Lecture Notes in Networks and Systems, vol 531. Springer, Cham. https://doi.org/10.1007/978-3-031-18050-7_37

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