Enhanced GO methodology to support failure mode, effects and criticality analysis-Reference-Cited by-同舟云学术

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Enhanced GO methodology to support failure mode, effects and criticality analysis

Published:2017-06-05 Issue:3 Volume:30 Page:1451-1468
ISSN:0956-5515
Container-title:Journal of Intelligent Manufacturing
language:en
Short-container-title:J Intell Manuf

Author:

Liu Linlin,Fan Dongming,Wang Zili,Yang Dezhen,Cui Jingjing,Ma Xinrui,Ren Yi

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Industrial and Manufacturing Engineering,Software

Link

http://link.springer.com/article/10.1007/s10845-017-1336-0/fulltext.html

Reference44 articles.

1. Beck, J. M., Ma, W. J., & Kiani, R. (2008). Probabilistic population codes for bayesian decision making. Neuron, 60(6), 1142–1152.

2. Bell, J., Snooke, N., & Price, C. (2007). A language for functional interpretation of model based simulation. Advanced Engineering Informatics, 21(4), 398–409.

3. Cantone, M., Tomarchio, E., & Veronese, I. (2016). A review of healthcare failure mode and effects analysis (HFMEA) in radiotherapy. Health Physics, 111, 317–326.

4. Carmignani, G. (2009). An integrated structu ral framework to cost-based FMECA: The priority-cost FMECA. Reliability Engineering and System Safety, 94, 861–871.

5. Castillo, E., Sarabia, J. M., & Solares, C. (1999). Uncertainty analyses in fault trees and Bayesian networks using FORM SORM methods. Reliability Engineering and Systems Safety, 65, 29–40.

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