12th International Symposium on Intelligent Distributed Computing
IDC 2018
15-17 October 2018, Bilbao, Spain

Sponsored by:



Latest news:

June 28th, 2018:
Registration is open

June 4th, 2018:
Updated notification deadline: June 5th, 2018

May 1st, 2018:
Submission deadline extended: May 15th, 2018 (no more extensions will be granted)

April 9, 2018:
Submission deadline extended: May 1st, 2018.

March 26, 2018:
New tutorial: ANDROPYTOOL.

March 6, 2018:
Confirmed Special Issue on Applied Soft Computing.

March 6, 2018:
New invited speaker: Albert Bifet.

January 19, 2018:
New Accepted Workshop: ML-PdM.

December 13, 2017:
New tutorial: JMETALSP.

December 13, 2017:
New tutorial: KMBD.

December 7, 2017:
New invited speakers: Francisco Herrera and Eleni I. Vlahogianni.

December 5, 2017:
New Accepted Workshop: COMPSUS.

November 15, 2017:
New Accepted Workshop: INDILOG.

November 6, 2017:
Confirmed Special Issue on Future Generation Computer Systems.

October 30, 2017:
Definitive conference dates published.

October 25, 2017:
Tentative conference dates published.

October 20, 2017:
First CFP published.

October 19, 2017:
Invited speakers: Jose A. Lozano and David Camacho.

October 18, 2017:
IDC 2018 web site was launched.

Workshop: Machine Learning methods applied to practical Predictive Maintenance problems (ML-PdM)

The increasing availability of data is changing the way decisions are taken in many fields, specially in the industry sector. In this context, machine learning (ML) approaches have shown to provide effective solutions for the management of maintenance activities, which are essential to minimize the high costs associated with failures, anomalies and/or defective products. With this in mind, the scientific community has been investigated new ML based techniques for appropriately tackling these type of problems, commonly referred to as predictive maintenance (PdM) problems. The solutions proposed in the literature ranges from detecting minor anomalies to failure patterns in order to determine the assets or processes that are at greatest risk of failure. The early identification of potential errors helps the deployment of more cost-effective resources, maximizing the equipment uptime and enhancing the quality of the processes and machines. Specifically, this workshop to be held during IDC2018 will gather researchers and practitioners to provide rich discussions around the latest findings, research achievements and ideas about predictive maintenance in the industry sector: wind/solar energy, automotive, manufacturing applications, and related sectors.

Topics of the special session include (but are not restricted to):

  • Recent advances on supervised and unsupervised classification techniques.
  • Novel applications on regression approaches for inferring the Remaining Useful Life (RUL).
  • Anomaly detection algorithms.
  • Application of neural networks, reinforcement learning, deep learning approaches for predictive maintenance problems.
  • Time series analysis for pattern detection.

with applications related to predictive maintenance.

Submission Guidelines

Interested colleagues are invited to submit novel contributions via the submission system. Only submissions with novel contributions with respect to the state of the art will be considered for inclusion in this session, i.e. workshop papers will be treated under the same criteria as regular conference papers.

All accepted papers will be included in the Symposium Proceedings, which will be published by Springer as part of their series Studies in Computational Intelligence.

Submission page: https://easychair.org/conferences/?conf=idc2018 (please add the prefix "ML-PdM:" to the title form field)

ML-PDM Organizers

  • Itziar Landa-Torres, TECNALIA, Spain (email)
  • Diana Manjarres, TECNALIA, Spain (email)

Program Committee

  • Ana Gonzalez-Marcos, University of La Rioja, Spain
  • Ali Sadollah, Sharif University of Technology, Iran
  • Eva Portillo, University of the Basque Country, Spain
  • Patricia Lopez, TEKNIKER, Spain
  • Leonardo Lopez, Universidad Tecnologica Federal de Parana, Brazil
  • Julio Elias Normey-Rico, Universidad Federal de Santa Catarina, Brazil
  • Juan Alejo Vazquez, University of Deusto, Spain
  • Xiao Zhang, Singapore University of Technology and Design, Singapore
  • Fernando Boto, TECNALIA, Spain
  • Alberto Diez, TECNALIA, Spain
  • Salvador Acha, Imperial College London, UK