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Miao Q.,University of Electronic Science and Technology of China | Liu L.,University of Electronic Science and Technology of China | Feng Y.,Institute of Aerospace equipment | Pecht M.,University of Maryland University College | Pecht M.,City University of Hong Kong
Microelectronics Reliability | Year: 2011

Complex system maintainability verification is always a challenging problem due to limited sample sizes. Consequently, conducting maintenance experiments in a laboratory environment is an appropriate way to obtain data for maintainability verification. In maintenance experiments, faults are seeded in the equipment and maintenance activities are implemented to record repair time. In this process, two problems arise when laboratory experimental data (in-lab data) are used together with field data during the operational test and evaluation stage. The first problem is the verification of segmental maintenance data and the second one is the combination of in-lab data and field data for integrative maintainability verification. Regarding the problems mentioned above, this paper proposes a suitable methodology to solve them. Firstly, the idea of segmentally weighted verification is adopted and the segmentally weighted verification (SWV) method is proposed to realize in-lab data verification. Secondly, the Dempster-Shafer (D-S) evidence theory based integrative verification method is presented to solve the problem of in-lab and field data combination. A case study concerning radar system maintainability verification is presented as an example of the implementation of complex system maintainability verification in industry. © 2010 Elsevier Ltd. All rights reserved. Source


Liu L.,University of Electronic Science and Technology of China | Miao Q.,University of Electronic Science and Technology of China | Feng Y.,Institute of Aerospace equipment
2010 Prognostics and System Health Management Conference, PHM '10 | Year: 2010

In the process of aero-equipment design and manufacturing, Mean Time to Repair (MTTR) is one of important maintainability parameters and it is required to conduct maintenance evaluation so as to verify equipment maintainability requirement. According GJB 2072 and MIL-STD-471 for aero-equipment maintenance evaluation, the number of samples should be no less than 30. However, it is almost impossible to obtain enough samples from field verification. It is necessary to utilize experimental data collected from laboratory environment as supplementary. By considering the differences between on field and laboratory data, this paper proposes a D-S evidence theory based maintenance integrated evaluation method to realize information fusion. The fused data can further be used for aero-equipment maintainability verification. © 2010 IEEE. Source

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