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[00788] Using multi-objective evolutionary algorithms when performing preventive maintenance actions

  • Session Time & Room : 3C (Aug.23, 13:20-15:00) @E820
  • Type : Industrial Contributed Talk
  • Abstract : Maintenance has always been a key activity in the manufacturing industry, because of its economic consequences. Nowadays, its importance is increasing thanks to the ``Industry 4.0'' or the ``fourth industrial revolution'', which promotes automation through computer systems in manufacturing and aims to achieve intelligent or smart factory. There are more and more complex systems to maintain, and to keep all these devices in proper conditions maintenance management must gain efficiency and effectiveness. Within maintenance, Condition-Based Maintenance (CBM) programs can provide significant advantages, but it can be said that often these programs are complex to manage and understand, so several researches propose as simple as possible approaches that can be understood by users and modified by experts. With these context conditions, this paper focuses on CBM optimization in an industrial environment, with the objective of determining the optimal values of preventive intervention limits for equipment under corrective and preventive maintenance cost criteria. It develops a cost-benefit mathematical model that considers the evolution in quality and production speed, along with condition based, corrective and preventive maintenance. The cost-benefit optimization is performed using a Multi-Objective Evolutionary Algorithm. Both the model and the optimization approach are applied to an industrial case.
  • Classification : 68W50, 68T20, 90C59
  • Format : Talk at Waseda University
  • Author(s) :
    • Eilsabete Alberdi (University of the Basque Country UPV/EHU)
    • Aitor Goti (University of Deusto)
    • Aitor Oyarbide-Zubillaga (University of Deusto)
    • Pablo Garcia-Bringas (University of Deusto)
    • Ana Sánchez (Polytechnic University of Valencia)