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Multi-attribute Ontology-based Criticality Analysis of manufacturing assets for maintenance strategies planning

机译:维修策略规划制造资产的基于多属性本体论的关键性分析

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Planning maintenance strategies in advance with respect to the installation and running of manufacturing assets positively affects operational expenditure during their usage. However, the early stages of the asset lifecycle are poor of operational data. Thus, domain knowledge of experts, related to the asset, the process and production requirements, is the primary source to determine which maintenance strategy better fits in a specific context. Hence, ontology-based systems represent a relevant help in this direction. In this work, given the importance of the criticality analysis (CA) for maintenance planning, the CA is analyzed from an ontological perspective to automatically associate a maintenance strategy to the asset under analysis. Moreover, to unveil the power of CA, its multi-attribute nature is considered, including not only availability as guiding criterion, but also quality and energy. The developed ontology-based CA allows to (i) semantically align all involved experts, and (ii) potentiate the analysis through reasoning capabilities. Finally, preliminary results from an industrial case in a food company are shown.
机译:规划维护战略提前对制造资产的安装和运行积极影响其使用期间的业务支出。但是,资产生命周期的早期阶段是糟糕的运营数据。因此,与资产,过程和生产要求相关的专家领域知识是确定哪种维护策略在特定上下文中更适合的主要来源。因此,基于本体的系统在此方向上表示相关的帮助。在这项工作中,鉴于对维护计划的关键性分析(CA)的重要性,从本体论的角度分析CA,以自动将维护策略与分析的资产相关联。此外,为了推出CA的力量,考虑其多属性,包括不仅可以作为指导标准的可用性,而且包括质量和能量。基于发发的本体的CA允许(i)通过推理能力进行语义对齐所有涉及的专家,并通过推理能力提高分析。最后,显示了食品公司工业案例的初步结果。

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