Name
Abstract | ||
|---|---|---|
Dependability modeling is a widely established method for analyzing the reliability of complex systems. Nearly all approaches focus on the representation - in success or failure space - of one specific system configuration. This does not reflect the high configurability of systems being common today. Furthermore, in order to perform a quantitative analysis of a model, the reliability engineer also needs to add exact event probabilities that can often only be estimated. Both things together lead to a situation where the final model may persuade the reader of an exactness that does not correspond with reality. We present an extended version of fault trees called Fuzz Trees. They combine fuzzy numbers for event probabilities with the modeling of system variability by new graphical notations. The concept allows the engineer to make uncertainty an explicit part of the dependability model, and to evaluate design alternatives early in the development. We discuss an initial analysis algorithm that allows the comparison of failure probabilities and costs for all possible system configurations being modeled by such a tree. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/PRDC.2013.48 | PRDC |
Keywords | Field | DocType |
final model,dependability modeling,specific system configuration,failure probability,complex system,system variability,possible system,dependability model,failure analysis,event probability,exact event probability,fault tree,fuzzy logic,reliability | Complex system,Notation,Dependability,Computer science,System configuration,Fuzzy logic,Theoretical computer science,Fault tree analysis,Fuzzy number,Reliability engineering,Distributed computing | Conference |
Citations | PageRank | References |
3 | 0.39 | 9 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Peter Tröger | 1 | 69 | 10.52 |
| Franz Becker | 2 | 3 | 0.39 |
| Felix Salfner | 3 | 430 | 22.55 |