Near-realtime analysis of test data for airframe certification

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KE-works is an SME. It is active in new product development for engineering-intensive manufacturing companies. The mission of KE-works is to improve significantly the operational efficiency of manufacturing through flexible and efficient product development processes. KE-works has a particular focus on the aerospace industry. Structural validation and certification of an airframe is inherently costly with high associated risks. To minimize the costs and risks it is crucial to detect the initiation of failure modes and the development of damage in a structure. This demands an ever growing number of measurement sensors with a corresponding increase in rates of data acquisition. 

Current test data analysis processes are inadequate for the large datasets that are currently captured. However, the use of cloud-based HPC now enable a near-realtime analysis of test data. This provides the ability to react and shift focus to problem areas in the structure, thereby significantly reducing the risks and costs of airframe certification tests. The objective of this case study is to develop a cloud-based HPC service for KE-works which provides two key capabilities: the first is near real-time failure mode detection during the static testing of airframes; and the second is trend monitoring and data analysis of fatigue test data for the full airframe.