Mechanical Structure Design Optimization by Blind Number Theory: Time-dependent Reliability

In a product development process, understanding the functional behavior of the system, the role of components in achieving functions and failure modes if components/subsystem fails its required function will help develop appropriate design validation and verification program for reliability assessment. The integration of these three issues will help design and reliability engineers in identifying weak spots in design and planning future actions and testing program. This case study demonstrate the advantage of unascertained theory described in the subjective cognition uncertainty, and then applies blind number (BN) theory in describing the uncertainty of the mechanical system failure process and the same time used the same theory in bringing out another mechanical reliability system model. The practical calculations shows the BN Model embodied the characters of simply, small account of calculation but betterforecasting capability, which had the value of macroscopic discussion to some extent.

• Zakari Yaou
• Lirong Cui

• Mechanical structure Design
• time-dependent stochastic process
• unascertained information
• blind number theory.

[1] O. Ditlevsen, Stochastic Model for Joint Wave and Wind Loads on Offshore Structures, Structural Safety, vol. 24, no. 2-4, pp. 139-163, Apr. 2002.
[2] J. P. Li, G. Thompson, A Method to Take Account of Inhomogeneity in
Mechanical Component Reliability calculations, IEEE Transaction on
Reliability, vol. 54, no. 1, pp. 159C168, Mar. 2005.
[3] J. S. R. Jayaram, T. Girish, Reliability Prediction through Degradation Data Modeling using a Quasi-likelihood Approach, in Proc. Annu. Reliab. Maintainability Symp 2005, Alexandria, VA, United states, 2005, pp. 193-199.
[4] W. Huang, R. G. Askin, A Generalized SSI Reliability Model Considering
Stochastic Loading and Strength Aging Degradation, IEEE Transactions
on Reliability, vol. 53, no. 1, pp. 77C82, Mar. 2004.
[5] L. Ruzhong. Multi-agent Blind Model and its Application to Regional
Eco-environmental Quality Assessmet. Chinese Geographical Science,
16(3), 2006.
[6] B. X. I. WAN Yu-cheng. The Analytic Hierarchy Process Based on the
Numascertained Information. Beijing. Fuzzy Information Processing Theories and Applications(FIP2003).
[7] S. S. J. ZHANG Yong-Qiang. Software Reliability Modeling Based on
Unascertained Theory. JOURNAL OF SOFTWARE, 17(8), 2006.
[8] H. H. CAI Liang, XIANG Tie-yuan. Blind-number model and indices
for power generating system reliability assessment. Power System Technology, 27(8), 2003.
[9] W. H. Liu Kaidi. Mathematics processing and application of uncertain
information. Science press, Beijing, 1999.