Examinando por Autor "Rezg, Nidhal"

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    Maintenance policy optimisation for multi-component systems considering degradation of components and imperfect maintenance actions
    (Elsevier Ltd, 2018-10-01) Martinod R, R.M.; Bistorin, Oliver; Castaneda Heredia Leonel F.; Rezg, Nidhal; Universidad EAFIT. Departamento de Ingeniería Mecánica; Estudios en Mantenimiento (GEMI)
    This article proposes a stochastic optimisation model in order to reduce the long-term total maintenance cost of complex systems. The proposed work is based on the following approaches: (i) optimisation of a cost model for complex multi-component systems consisting of preventive and corrective maintenance using reliability analysis, which faces two different maintenance policies (periodic block-type and age-based) and (ii) a clustering method for maintenance actions to decrease the total maintenance cost of the complex system. This work evaluates each maintenance policy and measures the effects on imperfect maintenance actions. Finally, the proposed optimisation model is applied to a numerical example which focuses on passenger urban aerial ropeway transport systems, in which the current maintenance policy has been evaluated, considering the established by the international regulation of passenger aerial cable cars. © 2018 Elsevier Ltd
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    RISK MANAGEMENT BASED ON FUZZY LOGIC FOR A FRANCIS TURBINE
    (EUROSIS, 2011-01-01) Mejia, Diego Tobon; Hennequin, Sophie; Botero, Francisco; Rezg, Nidhal; Castaneda, Leonel; Universidad EAFIT. Departamento de Ingeniería Mecánica; Estudios en Mantenimiento (GEMI)
    To facilitate the maintenance of hydroelectric groups and ensure the production of electrical energy, we defined a decision making tool to help the construction of maintenance plans by integrating the concept of risk for a Francis turbine currently operating in Colombia. As the risks are generally expressed in terms of human knowledge, it seems very interesting to use fuzzy logic to solve this kind of problems. Moreover, it can also be applied in case of detectable failures (via sensors) or undetectable failures. This work has been done in collaboration with EAFIT University in Colombia.