Name
Abstract | ||
|---|---|---|
Since some assumptions such as the function @f(.) needs to be completely specified and the relationship between @m and @f(s) must have linear behavior in the model @m=a+b@f(S) used in the accelerated life testing analysis, generally do not hold; the estimation of stress level contains uncertainty. In this paper, we propose to use a non-linear fuzzy regression model for performing the extrapolation process and adapting the fuzzy probability theory to the classical reliability including uncertainty and process experience for obtaining fuzzy reliability of a component. Results show, that the proposed model has the ability to estimate reliability when the mentioned assumptions are violated and uncertainty is implicit; so that the classical models are unreliable. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1016/j.asoc.2013.11.019 | Appl. Soft Comput. |
Keywords | Field | DocType |
classical model,degradation process,accelerated life testing analysis,classical reliability,process experience,fuzzy probability theory,linear behavior,fuzzy reliability,extrapolation process,non-linear fuzzy regression model,fuzzy numbers,accelerated life testing,reliability engineering | Mathematical optimization,Nonlinear system,Defuzzification,Fuzzy logic,Accelerated life testing,Extrapolation,Fuzzy regression,Fuzzy number,Degradation process,Mathematics | Journal |
Volume | ISSN | Citations |
16, | 1568-4946 | 6 |
PageRank | References | Authors |
0.51 | 9 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| David S. González | 1 | 33 | 5.84 |
| Rolando J. Praga-Alejo | 2 | 22 | 4.50 |
| Mario Cantú-Sifuentes | 3 | 10 | 2.29 |
| Luis M. Torres-Treviño | 4 | 26 | 11.49 |
| Gerardo M. Mendez | 5 | 181 | 12.74 |