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Data Mining and Knowledge Reuse for the Initial Systems Design and Manufacturing: Aero-engine Service Risk Drivers

机译:初始系统设计和制造中的数据挖掘和知识重用:航空发动机服务风险驱动因素

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Service providers of civil aero engines are typically confronted with a high cost of maintenance, replacement and refurbishment of the service damaged components. In such context, service experience becomes a key issue for determining the service risk drivers for operational disruptions and maintenance burden. This paper presents an industrial case study to produce new knowledge on the relationships between degradation and component design to manufacture. The study applied semantic data mining as a methodology for an efficient and the consistent data capture, representation, and analysis. The paper aims at identifying the service risk drivers based on service experience and event data. The analysis shows that the 3 top mechanisms accounting for 32% of the mechanism references have a strong Pareto effect. The paper concludes with missing information links and future research directions.
机译:民用航空发动机的服务提供商通常面临维修,更换和翻新服务受损部件的高昂费用。在这种情况下,服务经验成为确定服务风险驱动因素的关键问题,以决定运营中断和维护负担。本文提出了一个工业案例研究,以产生有关退化与要制造的零件设计之间关系的新知识。该研究将语义数据挖掘作为一种有效且一致的数据捕获,表示和分析的方法。本文旨在根据服务经验和事件数据确定服务风险驱动因素。分析表明,占机制参考的32%的3个顶级机制具有很强的帕累托效应。本文以缺少的信息链接和未来的研究方向作为结尾。

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