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A statistical approach to reduce failure facilities based on predictive maintenance

机译:一种基于预测性维护的减少故障设施的统计方法

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The aim of this study is to reduce the number of building facilities getting into failure efficiently based on predictive maintenance. These facilities diagnose their health states by time series sensing data and transmit event data to Monitoring Center (MC) as needed. In this paper, a statistical approach to determine when to dispatch maintenance workers is proposed. Firstly, the characteristic index is extracted from cumulative failure probability distribution using the event data. Secondly, the priority of the maintenance site visit for each facility is determined. Finally, the departure time of maintenance workers is calculated. Experimental results to evaluate whether the facilities can be maintained before failure occurs prove that this approach can reduce the number of failure facilities and mitigate the burden of maintenance workers.
机译:这项研究的目的是基于预测性维护,以有效减少发生故障的建筑设施的数量。这些设施通过时间序列感测数据诊断其健康状态,并根据需要将事件数据传输到监视中心(MC)。本文提出了一种确定何时派遣维修工人的统计方法。首先,使用事件数据从累积故障概率分布中提取特征指标。其次,确定每个设施的维护现场访问的优先级。最后,计算维修工人的离开时间。评估设施是否可以在故​​障发生之前进行维护的实验结果证明,该方法可以减少故障设施的数量并减轻维护人员的负担。

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