DocumentCode
3172168
Title
Improving system reliability with automatic fault tree generation
Author
Liggesmeyer, Peter ; Rothfelder, Martin
Author_Institution
Corp. Technol. Modeling & Simulation, Siemens AG, Munich, Germany
fYear
1998
fDate
23-25 June 1998
Firstpage
90
Lastpage
99
Abstract
Usually, fault tree analyses are performed manually. They are based on documents that describe the system. Considerable knowledge, system insight, and overview is necessary to consider many failure modes, and dependencies between system components and their functionality at a time. Often, the behavior is too complicated to fully comprehend all possible failure consequences. Manual fault tree analysis is error-prone, costly and not necessarily complete. Formal risk analysis, an approach for automatically generating a fault tree from finite state machine-based descriptions of a system, is presented. The generated fault tree is complete with respect to all failures assumed possible. It is the basis for subsequent improvements of the system design and quantitative analysis of safety and liveness requirements in the presence of failures. A case study of formal risk analysis, the automatic generation of a fault tree for all sensor failures of a production cell´s elevating rotary table, is discussed.
Keywords
fault tolerant computing; fault trees; finite state machines; industrial control; safety-critical software; sensors; automatic fault tree generation; computerised control; elevating rotary table; failure modes; fault tree analysis; finite state machine; formal risk analysis; liveness requirements; production cell; quantitative analysis; safety; sensor failure; system design; system reliability; Decision support systems; Fault trees; Reliability; Virtual reality;
fLanguage
English
Publisher
ieee
Conference_Titel
Fault-Tolerant Computing, 1998. Digest of Papers. Twenty-Eighth Annual International Symposium on
Conference_Location
Munich, Germany
ISSN
0731-3071
Print_ISBN
0-8186-8470-4
Type
conf
DOI
10.1109/FTCS.1998.689458
Filename
689458
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