Diego D'Urso

MatCarloRe: An integrated FT and Monte Carlo Simulink tool for the reliability assessment of dynamic fault tree

With the aim of a more effective representation of reliability assessment for real industry, in the last years concepts like dynamic fault trees (DFT) have gained the interest of many researchers and engineers (dealing with problems concerning safety management, design and development of new products, decision analysis and project management, maintenance of industrial plant, etc.). With the increased computational power of modern calculators is possible to achieve results with low modeling efforts and calculating time. Supported by the strong mathematical basis of state space models, the DFT technique has increased its popularity. Nevertheless, DFT analysis of real application has been more likely based on a specific case to case resolution procedure that often requires a great effort in terms of modeling by the human operator. Moreover, limitations like the state space explosion for increasing number of components, the constrain of using exponential distribution for all kind of basic events constituting any analyzed system and the ineffectiveness of modularization for DFT which exhibit dynamic gates at top levels without incurring in calculation and methodological errors are faces of these methodologies. In this paper we present a high level modeling framework that exceeds all these limitations, based on Monte Carlo simulation. It makes use of traditional DFT systemic modeling procedure and by replicating the true casual nature of the system can produce relevant results with low effort in term of modeling and computational time. A Simulink library that integrates Monte Carlo and FT methodologies for the calculation of DFT reliability has been developed, revealing new insights about the meaning of spare gates.

Dynamic fault trees resolution: A conscious trade-off between analytical and simulative approaches

Abstract Safety assessment in industrial plants with ‘major hazards’ requires a rigorous combination of both qualitative and quantitative techniques of RAMS. Quantitative assessment can be executed by static or dynamic tools of dependability but, while the former are not sufficient to model exhaustively time-dependent activities, the latter are still too complex to be used with success by the operators of the industrial field. In this paper we present a review of the procedures that can be used to solve quite general dynamic fault trees (DFT) that present a combination of the following characteristics: time dependencies, repeated events and generalized probability failure. Theoretical foundations of the DFT theory are discussed and the limits of the most known DFT tools are presented. Introducing the concept of weak and strong hierarchy, the well-known modular approach is adapted to study a more generic class of DFT. In order to quantify the approximations introduced, an ad-hoc simulative environment is used as benchmark. In the end, a DFT of an accidental scenario is analyzed with both analytical and simulative approaches. Final results are in good agreement and prove how it is possible to implement a suitable Monte Carlo simulation with the features of a spreadsheet environment, able to overcome the limits of the analytical tools, thus encouraging further researches along this direction.

A Weibull-based compositional approach for hierarchical dynamic fault trees

The solution of a dynamic fault tree (DFT) for the reliability assessment can be achieved using a wide variety of techniques. These techniques have a strong theoretical foundation as both the analytical and the simulation methods have been extensively developed. Nevertheless, they all present the same limits that appear with the increasing of the size of the fault trees (i.e., state space explosion, time-consuming simulations), compromising the resolution.

Conception of Repairable Dynamic Fault Trees and resolution by the use of RAATSS, a Matlab® toolbox based on the ATS formalism

Dynamic Fault Tree (DFT) is a well-known stochastic technique for conducting reliability studies of complex systems. At the state of the art, existing tools (both academic and commercial) do not fully support DFT with repairable components and repeated events, lowering the penetration of this powerful technique in real industrial applications (e.g., industrial processes and plants, computer, electronic and network applications). One of the main reasons limiting the attractiveness of DFT is that, originally, DFTs were conceived without repairable components; only recently few related works have started to deal with a formal semantic, which would avoid undefined behavior and misinterpretation of DFT. Other researchers have tackled the problem by introducing extensions of the original Fault Trees (FTs) technique like Boolean Driven Markov Processes (BDMPs) and Generalized Fault Trees (GFTs). However, despite they consider repairable systems and repeated events, we have found that the introduction of a different formalism with more complex features has again limited the penetration of these powerful methods in real applications. The target of this work is the original DFT technique. Starting from the state of the art, a set of standardized rules that frame the behaviors of dynamic gates are designed and a well-defined semantic for repairable-DFT is drawn through the application of a novel formalism, the Adaptive Transitions System (ATS). The proposed theoretical framework is afterward used to code a software tool, RAATSS, for the resolution of extended, repairable-DFT. Moreover, this work introduces some novel concepts regarding the modeling of a system by a DFT and provides a basic hint of the ATS capabilities to describe interdependencies in complex system.

An open-source application to model and solve dynamic fault tree of real industrial systems

In recent years, a new generation of modeling tools for the risk assessment have been developed. The concept of ¿dynamic¿ was exported also in the field of reliability and techniques like dynamic fault tree, dynamic reliability block diagrams, boolean logic driven Markov processes, etc., have become of use. But, despite the promises of researchers and the efforts of end-users, the dynamic paradox hangs: risk assessment procedures are not as straight as they were with the traditional static methods and, what is worse, it is difficult to assess the reliability of these results. Far from deny the importance of the scientific achievement, we have tested and cursed some of these dynamic tools realizing that none of them was appropriate to solve a real case. In this context, we decided to develop a new DFT reliability solver, based on the Monte Carlo simulative approach. The tool is greatly powerful because it is written with Matlab® code, hence is open-source and can be extended. In this first version, we have implemented the most used dynamic gates (PAND, SEQ, FDEP and SPARE), the existence of repeated events and the possibility to simulate different cumulative distribution function of failure (Weibull, negative exponential CDF and constant). The tool is provided with a snappy graphic user interface written in Java®, which allows an easy but efficient modeling of any fault tree schema. The tool has been tested with many literature cases of study and results encourage other developments.

SHyFTA, a Stochastic Hybrid Fault Tree Automaton for the modelling and simulation of dynamic reliability problems

Discussion about the state of the art of expert systems and reliability assessment.Formalisation of the Stochastic Hybrid Fault Tree Automaton modelling technique.Conception of Hybrid Basic Events.Experimental Comparison of DFT and SHyFTA model for an industrial case study.Implementation of the SHyFTA in Simulink using MatCarloRE library. Reliability assessment of industrial processes is traditionally performed with RAMS techniques. Such techniques are static in nature because they are unable to consider the multi-state operational and failure nature of systems and the dynamic variations of the environment in which they operate.Stochastic Hybrid Automaton appears to overcome this weakness coupling a deterministic and a stochastic process and integrating the features of a dynamic system with the concepts of dynamic reliability.At the state of the art, no attempts to enhance a formal RAMS technique with dynamic reliability has been tried, nor a computer-aided tool that plays as expert system has been coded yet.The aim of this paper is to fill this gap with a simulation formalism and a modelling tool able to combine the Dynamic Fault Tree technique and the Stochastic Hybrid Automaton within the Simulink environment. To this aim the MatCarloRE toolbox was adapted to interact with a Simulink dynamic system. The resulting assembly represents an important step ahead for the delivering of a user-friendly computer-aided tool for the dynamic reliability.

Coherence region of the Priority‐AND gate: Analytical and numerical examples

In recent years, the need for a more accurate dependability modelling (encompassing reliability, availability, maintenance, and safety) has favoured the emergence of novel dynamic dependability techniques able to account for temporal and stochastic dependencies of a system. One of the most successful and widely used methods is Dynamic Fault Tree that, with the introduction of the dynamic gates, enables the analysis of dynamic failure logic systems such as fault-tolerant or reconfigurable systems. Among the dynamic gates, Priority-AND (PAND) is one of the most frequently used gates for the specification and analysis of event sequences. Despite the numerous modelling contributions addressing the resolution of the PAND gate, its failure logic and the consequences for the coherence behaviour of the system need to be examined to understand its effects for engineering decision-making scenarios including design optimization and sensitivity analysis. Accordingly, the aim of this short communication is to analyse the coherence region of the PAND gate so as to determine the coherence bounds and improve the efficacy of the dynamic dependability modelling process.

Supporting group maintenance through prognostics-enhanced dynamic dependability prediction

Condition-based maintenance strategies adapt maintenance planning through the integration of online condition monitoring of assets. The accuracy and cost-effectiveness of these strategies can be improved by integrating prognostics predictions and grouping maintenance actions respectively. In complex industrial systems, however, effective condition-based maintenance is intricate. Such systems are comprised of repairable assets which can fail in different ways, with various effects, and typically governed by dynamics which include time-dependent and conditional events. In this context, system reliability prediction is complex and effective maintenance planning is virtually impossible prior to system deployment and hard even in the case of condition-based maintenance. Addressing these issues, this paper presents an online system maintenance method that takes into account the system dynamics. The method employs an online predictive diagnosis algorithm to distinguish between critical and non-critical assets. A prognostics-updated method for predicting the system health is then employed to yield well-informed, more accurate, condition-based suggestions for the maintenance of critical assets and for the group-based reactive repair of non-critical assets. The cost-effectiveness of the approach is discussed in a case study from the power industry.

A behavioural analysis of the newsvendor game: Anchoring and adjustment with and without demand information

Abstract Production systems are the combined result of technologies, organization, and individual behaviour. The impact of the human factor on the efficacy and efficiency of production systems is difficult to predict, since it often escapes the predictions of orthodox models of rationality. Recent behavioural studies in Operations Management highlight that the Human’s behaviour deviates from the optimal solution, even in simplified operating conditions such as those represented by the famous Newsvendor problem. Building on the results of controlled human experiments, this study proposes a decision-making model that accounts for the heuristics of anchoring and adjustment. Two experimental conditions, differing in the provision of demand information to decision makers, are used to generate data. The model estimated shows that anchoring and adjustment behaviour differs in the two conditions.

The Value-Analytic Hierarchy Process: a Lean Multi Criteria Decision Support Method

Abstract The Analytic Hierarchy Process uses pairwise comparison in order to define priorities for criteria and for alternatives, obtaining an overall ranking which represents a “rational decision”. In literature there are many examples of AHP applications where, in order to operate the ranking of alternatives according to qualitative and quantitative criteria, authors assign an utility value to the judgments on qualitative criteria but also to the values assumed on the basis of quantitative criteria. A modified approach, that was called Value-Analytic Hierarchy Process (V-AHP), was developed as a combination of traditional AHP rating on qualitative criteria and a “lean” rating on quantitative criteria. Such procedure allows to limit the use of the traditional AHP method only to criteria expressed by qualitative judgments and/or by scales different from ratio ones. A numerical example was carried out, according to the introduced methodology, in order to rank 15 potential simulated industrial investments evaluated by qualitative and quantitative criteria. The V-AHP can be defined a “lean” Multi Criteria Decision Support Method potentially applicable to any multi-criteria decision-making context.