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Optimal component-type allocation and replacement time policies for parallel systems having multi-types dependent components

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  • Additional Information
    • Contributors:
      Departamento de Análisis Económico: Economía Cuantitativa; Facultad de Ciencias Económicas y Empresariales
    • Publication Information:
      Elsevier
    • Publication Date:
      2022
    • Collection:
      Universidad Autónoma de Madrid (UAM): Biblos-e Archivo
    • Abstract:
      In this work, we discuss some challenging open problems and conjectures recently proposed in the literature for parallel systems with dependent components of multiple types. Specifically, we present necessary conditions for the existence of the unique optimal value which minimizes the mean cost rate for two optimization problems. In the first place, the aim is to find the optimal number of components of each type which minimizes the associated mean cost rate, and secondly, to find the optimal replacement time before system failure. In both cases, we consider copulas to model the dependence structure for components whose lifetimes follow any distribution function. Moreover, in order to illustrate the theoretical results, we provide some numerical studies for specific copulas and marginal distribution functions ; This work was partially supported by Ministerio de Ciencia e Innovación of Spain under grant number PID2019-108079GB-C22/AEI/ 10.13039/501100011033
    • File Description:
      application/pdf
    • Relation:
      Reliability Engineering and System Safety; https://doi.org/10.1016/j.ress.2022.108502; Gobierno de España. PID2019-108079GB-C22; Reliability Engineering and System Safety 224 (2022): 108502; https://hdl.handle.net/10486/704345; 224
    • Accession Number:
      10.1016/j.ress.2022.108502
    • Online Access:
      https://hdl.handle.net/10486/704345
      https://doi.org/10.1016/j.ress.2022.108502
    • Rights:
      © 2022 The Author ; Reconocimiento – NoComercial – SinObraDerivada ; open access
    • Accession Number:
      edsbas.855EF7CC