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Author: search.filters.author.Roberto Pérez-RodríguezHas files: Yes

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    Item type:Publication,
    Data-enabled Bayesian inference for strategic maintenance decisions in industrial operations
    (Elsevier BV, 2024-12)
    Raúl Torres-Sainz
    ;
    Leandro L. Lorente-Leyva
    ;
    Yorley Arbella-Feliciano
    ;
    Carlos Alberto Trinchet-Varela
    ;
    Lidia María Pérez-Vallejo
    Efficient management of industrial assets and equipment depends heavily on the selection of appropriate maintenance strategies. This research presents a dataset generated through Monte Carlo simulations to evaluate 12 key criteria relevant to maintenance strategy selection. The dataset covers a wide range of potential maintenance scenarios, providing comprehensive data for researchers to explore various strategies in industrial settings. The data were normalized and structured in a way that facilitates their use for further modeling or analysis. The dataset offers an opportunity for researchers to reproduce the data collection process, enabling comparisons with their own studies. By providing this dataset, we aim to support the development of new models for maintenance strategy selection and encourage further exploration of data-driven approaches in industrial maintenance. Additionally, the dataset can serve educational purposes, assisting in the teaching of decision-making in the context of maintenance operations.
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    Item type:Publication,
    Conceptual design vulnerability assessment of the housing light roofs to strong winds
    (Growing Science, 2024)
    Anabel Reyes-Ramírez
    ;
    Roberto Andrés Estrada-Cingualbres
    ;
    Libys Martha Zúñiga-Igarza
    ;
    Roberto Pérez-Rodríguez
    ;
    Leandro L. Lorente-Leyva
    Hurricanes are one of the most significant causes of human and material losses in the Caribbean region. These events have demonstrated their devastating impact on housing and infrastructure. The assessment of the vulnerability of buildings with light roofs, at the initial design stage, is considered to be a fundamental step in the mitigation of these damages and losses. This paper presents the introduction of an indicator-based vulnerability assessment in an effort to mitigate these damages in advance. This indicator facilitates the design team's decision to select the appropriate light roof alternative subject to strong winds at the conceptual stage of the process. The indicators that contribute to the conceptual assessment of vulnerability were identified based on a comprehensive review of the literature and numerical simulations of the risk scenarios using CFD/FEM software’s. The ranking of indicator weights was determined by the Kano method according to experts' opinions. A desktop application has been developed for the assessment of the vulnerability of light roof variants for buildings at the conceptual design stage. The results reported in a case study demonstrate the viability of the desktop application based on the vulnerability indicator to assist decision making in the conceptual design stage.