Name
Abstract | ||
|---|---|---|
Consequence reasoning is a major element for operation support system to assess the plant situations. The purpose of this paper is to elaborate how Multilevel Flow Models can be used to reason about consequences of disturbances in complex engineering systems. MFM is a modelling methodology for representing process knowledge for complex systems. It represents the system by using means-end and part-whole decompositions, and describes not only the purposes and functions of the system but also the causal relations between them. Thus MFM is a tool for causal reasoning. The paper introduces MFM modelling syntax and gives detailed reasoning formulas for consequence reasoning. The reasoning formulas offers basis for developing rule-based system to perform consequence reasoning based on MFM, which can be used for alarm design, risk monitoring, and supervision and operation support system design. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.3182/20130811-5-US-2037.00028 | IFAC Proceedings Volumes |
Keywords | Field | DocType |
Multilevel Flow Modelling,knowledge representation,functional modelling,consequence reasoning,rule-based system,decision support system | Complex system,Causal reasoning,Computer science,Causal relations,Model-based reasoning,Artificial intelligence,Reasoning system,Operations support system,Syntax,Qualitative reasoning | Conference |
Volume | Issue | ISSN |
46 | 15 | 1474-6670 |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xinxin Zhang | 1 | 0 | 1.69 |
| Morten Lind | 2 | 134 | 22.63 |
| Ole Ravn | 3 | 256 | 54.31 |