An optimal evaluating method for uncertainty metrics in reliability based on uncertain data envelopment analysis |
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| Affiliation: | 1. School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China;2. Science and Technology on Reliability and Environmental Engineering Laboratory, Beijing 100191, China;1. Institute of Rail Transit (IRT), Tongji University, Caoan 4800, Jiading, Shanghai 201804, China;2. Intel China Software Center (ICSC), Zixing Road 880, Zizhu Science Park, Shanghai 200240, China;1. School of Reliability and Systems Engineering, Beihang University, Beijing, China;2. Science and Technology on Reliability and Environmental Engineering Laboratory, Beihang University, Beijing, China;3. Data Center of China Life Insurance Company Ltd., Beijing, China;1. SEES, Depto. de Ingeniería Eléctrica, CINVESTAV-IPN, Av. IPN 2208, C.P. 07360 México City, Mexico.;2. Micro and Nanotechnology Research Centre, Universidad Veracruzana. Calzada Ruiz Cortines No. 455, Col. Costa Verde, C.P. 94294 Boca del Río, Veracruz, Mexico.;3. Materials Science and Engineering Department, University of Texas at Dallas, Richardson, TX 75080, United States |
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| Abstract: | In reliability engineering, there always exist uncertainties caused by the scarcity of data and information. Various metrics are developed to measure reliability under uncertainty, including evidence-theory-based reliability, interval-analysis-based reliability, fuzzy-interval-analysis-based reliability, posbist reliability and belief reliability. As these five metrics are difficult to be fully understood, it is hard to select the most appropriate one for a specific condition. This paper will propose an uncertain evaluating model to conduct an objective evaluation on these uncertainty metrics. An evaluating index system is established from the aspects of capabilities and adaptabilities. Uncertainty theory is adopted to deal with subjective uncertainties in the quantification process of the index system. Then an evaluating method based on uncertain data envelopment analysis is proposed to provide decision-makers with a succinct result for a given operational context. Finally, the evaluating method is illustrated with a numerical example, which shows that final metric choices vary with different requirements. |
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