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Bayesian Networks as a Support to Decision-Making When Evaluating Maintenance Scenarios
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作者 Daniela Ladiana Federico Novi Caterina Salvatori 《Journal of Civil Engineering and Architecture》 2020年第8期459-465,共7页
Contemporary architecture is characterized by an ever-greater morphological,functional and technological complexity.This requires new skills to effectively implement a process capable of ensuring an uninterrupted link... Contemporary architecture is characterized by an ever-greater morphological,functional and technological complexity.This requires new skills to effectively implement a process capable of ensuring an uninterrupted link between the concept of a building and its construction.The research described here focuses on implementing a tool for evaluating levels of maintenance quality applied at various stages in a project.In methodological terms,the research was conducted with the intention of constructing a system capable of managing the large number of variables involved in the design of a work of architecture from the earliest phases.The proposed digital model was defined through the construction and implementation of a Bayesian Network.The duration and maintainability of building components-generally expressed in statistical forecasts as expected duration in relation to operating conditions and as estimated costs and times of maintenance-were jointly evaluated using a synthetic index to generate a true overall rating of the various aspects that play a part in defining the quality of maintenance.The effectiveness of this decision-making support was tested in evaluations of complex architectural projects.Specifically,this text presents the results of an analysis of different maintenance scenarios for the ING Group Headquarters. 展开更多
关键词 maintenance-oriented design decision support system maintenance scenarios Bayesian networks rating system
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