• 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