Model-based dependability analysis : state-of-the-art, challenges and future outlook

Abstract: Over the past two decades, the study of model-based dependability analysis has gathered significant research interest. Different approaches have been developed to automate and address various limitations of classical dependability techniques to contend with the increasing complexity and challenges of modern safety-critical system. Two leading paradigms have emerged, one which constructs predictive system failure models from component failure models compositionally using the topology of the system. The other utilizes design models - typically state automata - to explore system behaviour through fault injection. This paper reviews a number of prominent techniques under these two paradigms, and provides an insight into their working mechanism, applicability, strengths and challenges, as well as recent developments within these fields. We also discuss the emerging trends on integrated approaches and advanced analysis capabilities. Lastly, we outline the future outlook for model-based dependability analysis

A synthesis of logic and bio-inspired techniques in the design of dependable systems

Much of the development of model-based design and dependability analysis in the design of dependable systems, including software intensive systems, can be attributed to the application of advances in formal logic and its application to fault forecasting and verification of systems. In parallel, work on bio-inspired technologies has shown potential for the evolutionary design of engineering systems via automated exploration of potentially large design spaces. We have not yet seen the emergence of a design paradigm that effectively combines these two techniques, schematically founded on the two pillars of formal logic and biology, from the early stages of, and throughout, the design lifecycle. Such a design paradigm would apply these techniques synergistically and systematically to enable optimal refinement of new designs which can be driven effectively by dependability requirements. The paper sketches such a model-centric paradigm for the design of dependable systems, presented in the scope of the HiP-HOPS tool and technique, that brings these technologies together to realise their combined potential benefits. The paper begins by identifying current challenges in model-based safety assessment and then overviews the use of meta-heuristics at various stages of the design lifecycle covering topics that span from allocation of dependability requirements, through dependability analysis, to multi-objective optimisation of system architectures and maintenance schedules

A Formal Transformation Method for Automated Fault Tree Generation from a UML Activity Model

Fault analysis and resolution of faults should be part of any end-to-end system development process. This paper is concerned with developing a formal transformation method that maps control flows modeled in UML Activities to semantically equivalent Fault Trees. The transformation method developed features the use of propositional calculus and probability theory. Fault Propagation Chains are introduced to facilitate the transformation method. An overarching metamodel comprised of transformations between models is developed and is applied to an understood Traffic Management System of Systems problem to demonstrate the approach. In this way, the relational structure of the system behavior model is reflected in the structure of the Fault Tree. The paper concludes with a discussion of limitations of the transformation method and proposes approaches to extend it to object flows, State Machines and functional allocations.Comment: 1st submission made to IEEE Transactions on Reliability on 27-Nov-2017; 2nd submission (revision) made on 27-Apr-2018. This version is the 2nd submission. 20 pages, 11 figure

A formal transformation method for automated fault tree generation from a UML activity model

IEEE Fault analysis and resolution of faults should be part of any end-to-end system development process. This paper is concerned with developing a formal transformation method that maps control flows modeled in unified modeling language activities to semantically equivalent fault trees. The transformation method developed features the use of propositional calculus and probability theory. Fault propagation chains are introduced to facilitate the method. An overarching metamodel comprised of transformations between models is developed and is applied to an understood traffic management system of systems problem to demonstrate the approach. In this way, the relational structure of the system behavior model is reflected in the structure of the fault tree. The paper concludes with a discussion of limitations of the transformation method and proposes approaches to extend it to object flows, state machines, and functional allocations

A Plausibility Semantics for Abstract Argumentation Frameworks

We propose and investigate a simple ranking-measure-based extension semantics for abstract argumentation frameworks based on their generic instantiation by default knowledge bases and the ranking construction semantics for default reasoning. In this context, we consider the path from structured to logical to shallow semantic instantiations. The resulting well-justified JZ-extension semantics diverges from more traditional approaches.Comment: Proceedings of the 15th International Workshop on Non-Monotonic Reasoning (NMR 2014). This is an improved and extended version of the author's ECSQARU 2013 pape

Machine learning and its applications in reliability analysis systems

In this thesis, we are interested in exploring some aspects of Machine Learning (ML) and its application in the Reliability Analysis systems (RAs). We begin by investigating some ML paradigms and their- techniques, go on to discuss the possible applications of ML in improving RAs performance, and lastly give guidelines of the architecture of learning RAs. Our survey of ML covers both levels of Neural Network learning and Symbolic learning. In symbolic process learning, five types of learning and their applications are discussed: rote learning, learning from instruction, learning from analogy, learning from examples, and learning from observation and discovery. The Reliability Analysis systems (RAs) presented in this thesis are mainly designed for maintaining plant safety supported by two functions: risk analysis function, i.e., failure mode effect analysis (FMEA) ; and diagnosis function, i.e., real-time fault location (RTFL). Three approaches have been discussed in creating the RAs. According to the result of our survey, we suggest currently the best design of RAs is to embed model-based RAs, i.e., MORA (as software) in a neural network based computer system (as hardware). However, there are still some improvement which can be made through the applications of Machine Learning. By implanting the 'learning element', the MORA will become learning MORA (La MORA) system, a learning Reliability Analysis system with the power of automatic knowledge acquisition and inconsistency checking, and more. To conclude our thesis, we propose an architecture of La MORA

Formal transformation methods for automated fault tree generation from UML diagrams

With a growing complexity in safety critical systems, engaging Systems Engineering with System Safety Engineering as early as possible in the system life cycle becomes ever more important to ensure system safety during system development. Assessing the safety and reliability of system architectural design at the early stage of the system life cycle can bring value to system design by identifying safety issues earlier and maintaining safety traceability throughout the design phase. However, this is not a trivial task and can require upfront investment. Automated transformation from system architecture models to system safety and reliability models offers a potential solution. However, existing methods lack of formal basis. This can potentially lead to unreliable results. Without a formal basis, Fault Tree Analysis of a system, for example, even if performed concurrently with system design may not ensure all safety critical aspects of the design. [Continues.]</div

Rules for the computer-aided synthesis of fault trees

This thesis describes the development of a computer-aided fault tree synthesis package for application in the process industries. It builds on the previous research work carried out in the Plant Engineering Group at Loughborough University. The emphasis has been put on describing the underlying methodology as opposed to the actual computer programs. The methodology described was developed by modelling a number of "real" systems, which had already been analysed using manual fault tree construction techniques by British Gas plc. Additionally a number of standard examples from the literature were utilised, as well as a large number of contrived examples to fully evaluate the package. The problems encountered and their solution are described. The culmination of this project was the implementation of the computer package at the Midlands Research Station of British Gas plc. It is not intended that the package should replace the fault tree expert. It should rather be viewed as a tool to facilitate the work of the process engineer, particularly during the design phase. This should enable the evaluation of many more options, which would otherwise have been proved prohibitive by the effort required to manually synthesise the fault trees

A system-theoretic, control-inspired view and approach to process safety

Accidents in the process industry continue to occur, and we do not seem to be making much progress in reducing them (Venkatasubramanian, 2011). Postmortem analysis has indicated that they were preventable and had similar systemic causes (Kletz, 2003). Why do we fail to learn from the past and make adequate changes to prevent their reappearance? A variety of explanations have been offered; operators' faults, component failures, lax supervision of operations, poor maintenance, etc. All of these explanations, and many others, have been exhaustively studied, analyzed, “systematized” into causal groups, and a variety of approaches have been developed to address them. Even so, they still occur with significant numbers of fatalities and injured people, with significant disruption of productive operations and frequently extensive destruction of the surrounding environment, both physical and social