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Making use of prognostics health management information for aerospace spare components logistics network optimisation

机译:利用预测健康管理信息进行航空航天备件物流网络优化

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摘要

Although research has evolved significantly over the last decade, there are still a large number of Grand Challenges confronting modelling, model deployment, and model-based decision making of large-scale complex Discrete Event Logistics Systems (DELS) to be tackled, as identified and reviewed during a Dagstuhl workshop in March 2010. This paper illustrates how several of these challenges are already being addressed, based on a series of case studies from the Aerospace Spare Components Logistics domain, where consolidated operational Prognostics and Health Management (PHM) information can be used for tactical planning and optimisation of spare components logistics networks. In this setting, the growing potential of PHM technology to facilitate the maintenance and support of commercial and military aircraft emphasises the need for tools to determine the impacts and benefits of a PHM system. To achieve this, the prognostics parameters and related logistics policies were identified, modelled, and subsequently incorporated into a simulation-based decision support framework.
机译:尽管在过去的十年中研究取得了长足的发展,但要确定,解决和解决的大型复杂离散事件物流系统(DELS)的建模,模型部署和基于模型的决策制定仍面临大量挑战。在2010年3月的Dagstuhl研讨会上进行了回顾。本文根据航空航天备件物流领域的一系列案例研究,说明了如何应对其中的一些挑战,在这些案例研究中,可以将合并的运营预测和健康管理(PHM)信息用于战术计划和零件备件物流网络的优化。在这种情况下,PHM技术在促进商用和军用飞机的维护和支持方面的潜力日益增长,这凸显了对确定PHM系统影响和收益的工具的需求。为此,对预测参数和相关的物流策略进行了识别,建模,然后将其纳入基于模拟的决策支持框架中。

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