A linear-time algorithm to find modules of fault trees

Dutuit, Yves; Rauzy, Antoine

doi:10.1109/24.537011

Cited by 136 publications

(83 citation statements)

References 8 publications

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“…Fault trees were simplified [7] prior to BDD conversion process. The simplification process contains the reduction [8] and modularisation [9] techniques. It allows a more efficient analysis of fault trees.…”

Section: Comparison Of the Methodsmentioning

confidence: 99%

An enhanced component connection method for conversion of fault trees to binary decision diagrams

Remenyte‐Prescott¹,

Andrews²

2008

Reliability Engineering & System Safety

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A note on versions:The version presented here may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the repository url above for details on accessing the published version and note that access may require a subscription.For more information, please contact eprints@nottingham.ac.uk An Enhanced Component Connection Method for Conversion of Fault Trees toBinary Decision Diagrams R. Remenyte-Prescott; Prof. J.D. Andrews AbstractFault Tree Analysis (FTA) is widely applied to assess the failure probability of industrial systems. Many computer packages are available which are based on conventional Kinetic Tree Theory methods. When dealing with large (possibly non-coherent) fault trees, the limitations of the technique in terms of accuracy of the solutions and the efficiency of the processing time becomes apparent. Over recent years the Binary Decision Diagram (BDD) method has been developed that solves fault trees and overcomes the disadvantages of the conventional FTA approach. First of all, a fault tree for a particular system failure mode is constructed and then converted to a BDD for analysis. This paper analyses alternative methods for the fault tree to BDD conversion process.For most fault tree to BDD conversion approaches the basic events of the fault tree are placed in an ordering. This can dramatically affect the size of the final BDD and the success of qualitative and quantitative analyses of the system. A set of rules are then applied to each gate in the fault tree to generate the BDD. An alternative approach can also be used, where BDD constructs for each of the gate types are first built and then merged to represent a parent gate. A powerful and efficient property, sub-node sharing, is also incorporated in the enhanced method proposed in this paper. Finally a combined approach is developed taking the best features of the alternative methods. The efficiency of the techniques is analysed and discussed.Keywords: Fault Tree Analysis, Binary Decision Diagrams IntroductionThe Binary Decision Diagram (BDD) method [1] has been introduced as a method for efficient and accurate fault tree analysis. This method has been shown to have advantages over the conventional Kinetic Tree Theory [2]. The main strength of the BDD method is the fact that top event probabilities can be calculated without the need to apply approximations or the need to obtain minimal cut sets as intermediate results.In the BDD method the fault tree is converted to a binary decision diagram, which represents the Boolean logic expression of the particular system failure mode. The method requires to set the variable ordering, and if it is not chosen suitably, the size of the final BDD can grow exponentially. The ordering rules are then applied to construct the BDD (ite method [1]). Alternative conversion methods are presented in this paper. These include component connection methods [3] where BDDs for each of the gate types are formed and then ...

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Section: Comparison Of the Methodsmentioning

confidence: 99%

An enhanced component connection method for conversion of fault trees to binary decision diagrams

Remenyte‐Prescott¹,

Andrews²

2008

Reliability Engineering & System Safety

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“…A subtree M is structurally independent if all the events in M belong to subtrees included in M or to subtrees including M . If we ignore the RBs and their arcs, the structural independent subtrees in a GFT, can be identified by applying the modules detection algorithm developed for FTs [14]. This algorithm consists of a depth-first left-most visit of the model, starting from the TE and assuming the opposite orientation of the arcs.…”

Section: Modules Detectionmentioning

confidence: 99%

Integrating several formalisms in order to increase Fault Trees' modeling power

Codetta‐Raiteri

2011

Reliability Engineering & System Safety

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The Fault Tree (FT) is a widespread model in the field of Reliability, but its modeling power is very limited. Therefore several FT extensions have been proposed in the literature, each introducing particular modeling primitives, but in a separate way. In this paper, we integrate the primitives coming from three relevant FT extensions (Parametric, Dynamic, and Repairable FT), into the formalism called Generalized FT (GFT). We define each primitive in such a way that it can be combined with any other one. This allows to compactly represent redundancies and symmetries of the system structure, set several kinds of dependency among the events, and model repair processes, in the same model. The paper provides also an analysis process for GFT models based on the modular approach. In particular, we provide the conditions to detect modules, considering the presence of all the primitives. Besides modules, we exploit the parametric form also at the solution level, with the aim of reducing the cost of analysis.

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“…An efficient method of calculating the criticality function from the BDD (7) considers the probabilities of the path sections of the BDD up to and after the nodes in question, resulting in the following expression: (4) where:…”

Section: System Unconditional Failure Intensitymentioning

confidence: 99%

“…The initial stage combines two simplification techniques that have been shown to be advantageous in the construction of BDDs: Faunet reduction (3) , and linear-time modularisation (4) . The reduction technique reduces the fault tree to its minimal logic form, whilst modularisation identifies independent subtrees (modules) existing within the tree that can be analysed separately.…”

Section: Introductionmentioning

confidence: 99%