System safety, reliability and risk analysis are important tasks that are performed throughout the system lifecycle to ensure the dependability of safety-critical systems. Probabilistic risk assessment (PRA) approaches are comprehensive, structured and logical methods widely used for this purpose. PRA approaches include, but not limited to, Fault Tree Analysis (FTA), Failure Mode and Effects Analysis (FMEA), and Event Tree Analysis (ETA). Growing complexity of modern systems and their capability of behaving dynamically make it challenging for classical PRA techniques to analyse such systems accurately. For a comprehensive and accurate analysis of complex systems, different characteristics such as functional dependencies among components, temporal behaviour of systems, multiple failure modes/states for components/systems, and uncertainty in system behaviour and failure data are needed to be considered. Unfortunately, classical approaches are not capable of accounting for these aspects. Bayesian networks (BNs) have gained popularity in risk assessment applications due to their flexible structure and capability of incorporating most of the above mentioned aspects during analysis. Furthermore, BNs have the ability to perform diagnostic analysis. Petri Nets are another formal graphical and mathematical tool capable of modelling and analysing dynamic behaviour of systems. They are also increasingly used for system safety, reliability and risk evaluation. This paper presents a review of the applications of Bayesian networks and Petri nets in system safety, reliability and risk assessments. The review highlights the potential usefulness of the BN and PN based approaches over other classical approaches, and relative strengths and weaknesses in different practical application scenarios.

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The scale and complexity of computer-based safety critical systems, like those used in the transport and manufacturing industries, pose significant challenges for failure analysis. Over the last decade, research has focused on automating this task. In one approach, predictive models of system failure are constructed from the topology of the system and local component failure models using a process of composition. An alternative approach employs model-checking of state automata to study the effects of failure and verify system safety properties.In this paper, we discuss these two approaches to failure analysis. We then focus on Hierarchically Performed Hazard Origin and Propagation Studies (HiP-HOPS) -one of the more advanced compositional approaches -and discuss its capabilities for automatic synthesis of fault trees, combinatorial Failure Modes and Effects Analyses, and reliability versus cost optimisation of systems via application of automatic model transformations.We summarise these contributions and demonstrate the application of HiP-HOPS on a simplified fuel oil system for a ship engine. In light of this example, we discuss strengths and limitations of the method in relation to other state-of-the-art techniques. In particular, because HiP-HOPS is deductive in nature, relating system failures back to their causes, it is less prone to combinatorial explosion and can more readily be iterated. For this reason, it enables exhaustive assessment of combinations of failures and design optimisation using computationally greedy meta-heuristics.

Safety and reliability are rigorously assessed during the design of dependable systems. Probabilistic risk assessment (PRA) processes are comprehensive, structured and logical methods widely used for this purpose. PRA approaches include, but not limited to Fault Tree Analysis (FTA), Failure Mode and Effects Analysis (FMEA), and Event Tree Analysis (ETA). In conventional PRA, failure data about components is required for the purposes of quantitative analysis. In practice, it is not always possible to fully obtain this data due to unavailability of primary observations and consequent scarcity of statistical data about the failure of components. To handle such situations, fuzzy set theory has been successfully used in novel PRA approaches for safety and reliability evaluation under conditions of uncertainty. This paper presents a review of fuzzy set theory based methodologies applied to safety and reliability engineering, which include fuzzy FTA, fuzzy FMEA, fuzzy ETA, fuzzy Bayesian networks, fuzzy Markov chains, and fuzzy Petri nets. Firstly, we describe relevant fundamentals of fuzzy set theory and then we review applications of fuzzy set theory to system safety and reliability analysis. The review shows the context in which each technique may be more appropriate and highlights the overall potential usefulness of fuzzy set theory in addressing uncertainty in safety and reliability engineering.

The Fault Tree Handbook has become the de facto standard for Fault Tree Analysis (FTA), defining the notation and mathematical foundation of this widely used safety analysis technique. The Handbook recognises that classical combinatorial fault trees employing only Boolean gates cannot capture the potentially critical significance of the temporal ordering of failure events in a system. Although the Handbook proposes two dynamic gates that could remedy this, a Priority-AND and an Exclusive-OR gate, these gates were never accurately defined. In this paper, we propose extensions to the logical foundation of fault trees that enable use of these dynamic gates in an extended and more powerful FTA. The benefits of this approach are demonstrated on a generic triple-module standby redundant system exhibiting dynamic behaviour.

Purpose – The purpose of this paper (based on the relevant literature) is to: investigate, through empirical analysis, primary school teachers’ perceptions regarding their job satisfaction, and examine whether or not the personal characteristics of primary school educators (such as gender, age, family status, educational level, and the total years of service in public primary education) have any impact on their job satisfaction. Design/methodology/approach – In total, 360 questionnaires were administered to primary school teachers in the metropolitan area of Athens (region of Attiki). The sample was randomly selected. The questionnaire was based on 41 closed and was divided into two sections. The Job Satisfaction Survey developed by Spector (1985) was implemented. Findings – Greek school teachers are generally satisfied with their profession. There is no statistical correlation between personal characteristics and the overall satisfaction while indicated that teachers are more satisfied with three aspects (subscales) of job satisfaction, namely, “administration,” “colleagues” and “nature of work” and less satisfied with “salary,” “benefits” and “potential rewards.” Age correlates with the levels of satisfaction with reference to administration, potential rewards, colleagues and the nature of work. The overall satisfaction positively correlates with all nine aspects of job satisfaction (subscales) and gender affects the aspects of “promotion” and “colleagues.” Research limitations/implications – This study only analyzes a small sample from the Athens region and hence the results cannot be used to generalize about the whole of Greece. Since other Greek regions operate in different socio-economic environments, an analysis of additional data from other regions (rural and urban areas) would be necessary to compare and confirm the results. Originality/value – The findings of this study a valuable extension of other relevant research as it provides the first empirical study of the Greek school system, investigating the relationship between certain aspects of job satisfaction and the personal characteristics of school educators as well as the relationship between these aspects of job satisfaction and total satisfaction. In the context of efficient educational policy, a greater understanding of educators’ job satisfaction could facilitate the development of more effective policy practice that would increase not only the level of educators’ satisfaction, commitment and morale but also improve the performance of the school system.

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