A Predictive Maintenance Model Using Recurrent Neural Networks

  • Alberto RivasEmail author
  • Jesús M. Fraile
  • Pablo Chamoso
  • Alfonso González-Briones
  • Inés Sittón
  • Juan M. Corchado
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 950)


One of the main goals of Industry 4.0 is to anticipate machine breakdowns. Being able to prevent failures is important because downtime implies high cost and production loss. For this reason, the calculation of the number of remaining cycles or Remaining Useful Life (RUL) until a breakdown occurs is essential for machine maintenance. The calculation of the RUL should be based on previous observations, if possible under the same conditions. Research on RUL estimation has become central to the development of systems that monitor the current state of machines. Although this field has been studied in-depth, there is no single universal method. The lack of a universal method is the motivation behind this proposal in which the designed system uses recurrent neural networks (RNN) in a predictive maintenance problem.


Remaining useful life Recurrent neural network Predictive maintenance Industry 4.0 



This research has been partially supported by the European Regional Development Fund (ERDF) under the IOTEC project grant 0123_IOTEC_3_E and by the Spanish Ministry of Economy, Industry and Competitiveness.


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Alberto Rivas
    • 1
    Email author
  • Jesús M. Fraile
    • 1
  • Pablo Chamoso
    • 1
  • Alfonso González-Briones
    • 1
  • Inés Sittón
    • 1
  • Juan M. Corchado
    • 1
    • 2
    • 3
    • 4
  1. 1.BISITE Research Group, University of SalamancaSalamancaSpain
  2. 2.Air Institute, IoT Digital Innovation Hub (Spain)SalamancaSpain
  3. 3.Department of Electronics, Information and Communication, Faculty of EngineeringOsaka Institute of TechnologyOsakaJapan
  4. 4.Pusat Komputeran dan InformatikUniversiti Malaysia KelantanKota BharuMalaysia

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