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Proceedings of the International Conference on Sustainable Design and Manufacturing

KES-SDM 2021: Sustainable Design and Manufacturing pp 12–23Cite as

Prevention of Failures in the Footwear Production Process by Applying Machine Learning

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Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 262))

Abstract

At present, the handcrafted footwear sector is affected by the high competitiveness due to the increasing automation of companies. In this sense, in order to improve its competitiveness, a system was proposed to predict the failures of a production system and to carry out preventive maintenance actions. Samples were taken from 25 productions and 7 activities were established: cutting, stitching, pre fabrication, final preparation, gluing, assembly and finishing. The company produces batches of 90 pairs per day, with a standard time of 274.53 min and a promised productivity of 1.8. A support vector machine model was developed to predict the possible failures of the process taking as a reference the standard time of each stage. Finally, the results allow predicting the faults to optimise the production process by applying Support Vector Machine (SVM).

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Author information

Authors and Affiliations

  1. SISAu Research Group, Facultad de Ingeniería y Tecnologías de la Información y Comunicación, Universidad Tecnológica Indoamérica, Ambato, Ecuador

    Marcelo Tierra-Arévalo, Manuel Ayala-Chauvin & Carmen Nacevilla

  2. Centro de Diseño de Equipos Industriales, Universidad Politécnica de Cataluña, Barcelona, Spain

    Albert de la Fuente-Morato

Authors
  1. Marcelo Tierra-Arévalo
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  2. Manuel Ayala-Chauvin
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  3. Carmen Nacevilla
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  4. Albert de la Fuente-Morato
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Corresponding author

Correspondence to Manuel Ayala-Chauvin .

Editor information

Editors and Affiliations

  1. Karlsruhe Institute of Technology, Karlsruhe, Germany

    Steffen G. Scholz

  2. KES International, Shoreham-by-Sea, UK

    Robert J. Howlett

  3. Cardiff University, Cardiff, UK

    Rossi Setchi

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Tierra-Arévalo, M., Ayala-Chauvin, M., Nacevilla, C., de la Fuente-Morato, A. (2022). Prevention of Failures in the Footwear Production Process by Applying Machine Learning. In: Scholz, S.G., Howlett, R.J., Setchi, R. (eds) Sustainable Design and Manufacturing. KES-SDM 2021. Smart Innovation, Systems and Technologies, vol 262. Springer, Singapore. https://doi.org/10.1007/978-981-16-6128-0_2

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  • DOI: https://doi.org/10.1007/978-981-16-6128-0_2

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-6127-3

  • Online ISBN: 978-981-16-6128-0

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