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Stochastic overall equipment effectiveness

机译:随机总体设备效率

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This article focuses on the overall equipment effectiveness (OEE), a key performance indicator typically adopted to support Lean Manufacturing and Total Productive Maintenance. Unfortunately, being a deterministic metric, the OEE only provides a static representation of a process, but fails to capture the real variability of manufacturing performances. To take into account the stochastic nature of the OEE, an approximated procedure based on the application of the Central Limit Theorem is presented: the OEE is considered as a stochastic random variable and its probability density function (pdf) is generated through the aggregation of the pdf of the basic causes of waste. Notwithstanding its approximated nature, the procedure can be applied in most practical cases, since the accuracy is assured provided that the average OEE is lower than 90% and the variability of the losses is high. The validity of the approach has also been confirmed by an industrial application included in this article. The results obtained demonstrate that the stochastic OEE can help in battling variation, for it allows one to identify the hidden losses that account for most of the variability and to estimate the impacts of potential corrective actions in terms of both efficiency and efficacy.
机译:本文重点介绍总体设备效率(OEE),这是通常用于支持精益生产和全面生产维护的关键性能指标。不幸的是,OEE作为确定性指标,仅提供过程的静态表示,而无法捕获制造性能的真实变化。考虑到OEE的随机性,提出了基于中央极限定理的应用的近似过程:OEE被认为是随机随机变量,其概率密度函数(pdf)通过对pdf浪费的基本原因。尽管具有近似性质,但该程序可用于大多数实际情况,因为只要平均OEE低于90%并且损失的可变性较高,就可以保证准确性。本文中包含的工业应用也已经证实了该方法的有效性。获得的结果表明,随机OEE可以帮助应对变化,因为它可以使人们识别出造成大多数变化的隐性损失,并从效率和功效两方面评估潜在的纠正措施的影响。

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