Yes / The agricultural industry has the potential to undergo a revolutionary transformation with the use of Internet of Things (IoT) technology. Crop monitoring can be improved, waste reduced, and efficiency increased. However, there are risks associated with system failures that can lead to significant losses and food insecurity. Therefore, a proactive approach is necessary to ensure the effective safety assessment of new IoT systems before deployment. It is crucial to identify potential causes of failure and their severity from the conceptual design phase of the IoT system within smart agricultural ecosystems. This will help prevent such risks and ensure the safety of the system. This study examines the failure behaviour of IoT-based Smart Irrigation Systems (SIS) to identify potential causes of failure. This study proposes a comprehensive Model-Based Safety Analysis (MBSA) framework to model the failure behaviour of SIS and generate analysable safety artefacts of the system using System Modelling Language (SysML). The MBSA approach provides meticulousness to the analysis, supports model reuse, and makes the development of a Fault Tree Analysis (FTA) model easier, thereby reducing the inherent limitations of informal system analysis. The FTA model identifies component failures and their propagation, providing a detailed understanding of how individual component failures can lead to the overall failure of the SIS. This study offers valuable insights into the interconnectedness of various component failures by evaluating the SIS failure behaviour through the FTA model. This study generates multiple minimal cut sets, which provide actionable insights into designing dependable IoT-based SIS. This analysis identifies potential weak points in the design and provides a foundation for safety risk mitigation strategies. This study emphasises the significance of a systematic and model-driven approach to improving the dependability of IoT systems in agriculture, ensuring sustainable and safe implementation.

Yes / Fuzzy data-driven reliability analysis has been used in different safety-critical domains for risk assessment and decision-making where precise failure data is non-existent. Expert judgements and fuzzy set theory have been combined with different variants of fault trees as part of fuzzy data-driven reliability analysis studies. In such fuzzy fault tree analyses, different people represented failure data using different membership functions for the fuzzy set, and different parameters were set differently in the expert opinion elicitation process. Due to the availability of a wide variety of options, it is possible to obtain different outcomes when choosing one option over another. This article performed an analysis in the context of fuzzy data-based temporal fault tree analysis to investigate the effect of choosing different membership functions on the estimated system reliability and criticality ranking of different failure events. Moreover, the effect of using different values for the relaxation factor, a parameter set during the expert elicitation process, was studied on the system reliability and criticality evaluation. The experiments on the fuel distribution system case study show system reliability did not vary when triangular and trapezoidal fuzzy numbers were used with the same upper and lower bounds. However, it was seen that the criticality rankings of a couple of events were changed due to choosing different membership functions and different values of relaxation factor

Yes / Fault Tree Analysis (FTA) is a well-established and well-understood technique, widely used for dependability evaluation of a wide range of systems. Although many extensions of fault trees have been proposed, they suffer from a variety of shortcomings. In particular, even where software tool support exists, these analyses require a lot of manual effort. Over the past two decades, research has focused on simplifying dependability analysis by looking at how we can synthesise dependability information from system models automatically. This has led to the field of model-based dependability analysis (MBDA). Different tools and techniques have been developed as part of MBDA to automate the generation of dependability analysis artefacts such as fault trees. Firstly, this paper reviews the standard fault tree with its limitations. Secondly, different extensions of standard fault trees are reviewed. Thirdly, this paper reviews a number of prominent MBDA techniques where fault trees are used as a means for system dependability analysis and provides an insight into their working mechanism, applicability, strengths and challenges. Finally, the future outlook for MBDA is outlined, which includes the prospect of developing expert and intelligent systems for dependability analysis of complex open systems under the conditions of uncertainty.

Les analyses de sûreté de fonctionnement standards sont basées sur la représentation des événements redoutés par des arbres de défaillances, qui les décrivent à l'aide de combinaison logiques d'événements plus basiques (formules Booléennes complexes). Les analyses quantitatives se font avec l'hypothèse que les probabilités d'occurrence de ces événements basiques sont connues. Le but de cette thèse est d'étudier l'impact de l'incertitude épistémique sur les événements élémentaires, ainsi que la propagation de cette incertitude à de plus hauts niveaux. Le problème soulevé est comment calculer l'intervalle de probabilité dans lequel se trouvera l'occurrence d'un événement redouté, lorsque les événements basiques qui le décrivent ont eux-mêmes une probabilité imprécise. Lorsque l'indépendance stochastique est supposée, on se retrouve avec un problème NP-hard. Nous avons donc développé un algorithme permettant de calculer l'intervalle exact dans lequel se trouvera la probabilité d'occurrence d'un événement redouté, grâce à des techniques d'analyse par intervalles. Cet algorithme a également été étendu dans le cas où les probabilités des événements basiques évolueraient en fonction du temps. Nous avons également utilisé une approche par fonctions de croyance pour étudier le cas où l'indépendance stochastique des événements ne peut pas être démontrée : on suppose alors que les probabilités viennent de différentes sources d'information Indépendantes. Dans ce cas, les mesures de plausibilité et de nécessité d'une formule Booléenne complexe sont difficiles à calculer, néanmoins nous avons pu dégager des situations pratiques dans le cadre de leur utilisation pour les Arbres de défaillances pour lesquelles elles se prêtent aux calculs. / Standard approaches to reliability analysis relies on a probabilistic analysis of critical events based on fault tree representations. However in practice, and especially for preventive maintenance tasks, the probabilities ruling the occurrence of these events are seldom precisely known. The aim of this thesis is to study the impact of epistemic uncertainty on probabilities of elementary events such as failures over the probability of some higher level critical event. The fundamental problem addressed by the thesis is thus to compute the probability interval for a Boolean proposition representing a failure condition, given the probability intervals of atomic propositions. When the stochastic independence is assumed, we face a problem of interval analysis, which is NP-hard in general. We have provided an original algorithm that computes the output probability interval exactly, taking into account the monotonicity of the obtained function in terms of some variables so as to reduce the uncertainty. We have also considered the evolution of the probability interval with time, assuming parameters of the reliability function to be imprecisely known. Besides, taking advantage of the fact that a probability interval on a binary space can be modelled by a belief function, we have solved the same problem with a different assumption, namely information source independence. While the problem of computing the belief and plausibility of a Boolean proposition are even harder to compute, we have shown that in practical situations such as usual fault-trees, the additivity condition of probability theory is still valid, which simplifies this calculation. A prototype has been developed to compute the probability interval for a complex Boolean proposition.

Information technology has become increasingly important to individuals and organizations alike. Not only does IT allow us to do what we always did faster and more effectively, but it also allows us to do new things, organize ourselves differently, and work in ways previously unimaginable. However, these advantages come at a cost: as we become increasingly dependent upon IT services, we also demand that they are continuously and uninterruptedly available for use. Despite advances in reliability engineering, the complexity of today's increasingly integrated systems offers a non-trivial challenge in this respect. How can high availability of enterprise IT services be maintained in the face of constant additions and upgrades, decade-long life-cycles, dependencies upon third-parties and the ever-present business-imposed requirement of flexible and agile IT services? The contribution of this thesis includes (i) an enterprise architecture framework that offers a unique and action-guiding way to analyze service availability, (ii) identification of causal factors that affect the availability of enterprise IT services, (iii) a study of the use of fault trees for enterprise architecture availability analysis, and (iv) principles for how to think about availability management. This thesis is a composite thesis of five papers. Paper 1 offers a framework for thinking about enterprise IT service availability management, highlighting the importance of variance of outage costs. Paper 2 shows how enterprise architecture (EA) frameworks for dependency analysis can be extended with Fault Tree Analysis (FTA) and Bayesian networks (BN) techniques. FTA and BN are proven formal methods for reliability and availability modeling. Paper 3 describes a Bayesian prediction model for systems availability, based on expert elicitation from 50 experts. Paper 4 combines FTA and constructs from the ArchiMate EA language into a method for availability analysis on the enterprise level. The method is validated by five case studies, where annual downtime estimates were always within eight hours from the actual values. Paper 5 extends the Bayesian prediction model from paper 3 and the modeling method from paper 4 into a full-blown enterprise architecture framework, expressed in a probabilistic version of the Object Constraint Language. The resulting modeling framework is tested in nine case studies of enterprise information systems. / Informationsteknik blir allt viktigare för både enskilda individer och för organisationer. IT låter oss inte bara arbeta snabbare och effektivare med det vi redan gör, utan låter oss också göra helt nya saker, organisera oss annorlunda och arbeta på nya sätt. Tyvärr har dessa fördelar ett pris: i takt med att vi blir alltmer beroende av IT-tjänster ökar också våra krav på att de är ständigt tillgängliga för oss, utan avbrott. Trots att tillförlitlighetstekniken går framåt utgör dagens alltmer sammankopplade system en svår utmaning i detta avseende. Hur kan man säkerställa hög tillgänglighet hos IT-tjänster som ständigt byggs ut och uppgraderas, som har livscykler på tiotals år, som är beroende av tredjepartsleverantörer och som dessutom måste leva upp till verksamhetskrav på att vara flexibla och agila? Den här avhandlingen innehåller (i) ett arkitekturramverk som på ett unikt sätt kan analysera IT-tjänsters tillgänglighet och ta fram rekommenderade åtgärder, (ii) ett antal identifierade kausalfaktorer som påverkar IT-tjänsters tillgänglighet, (iii) en studie av hur felträd kan användas för arkitekturanalys av tillgänglighet samt (iv) en uppsättning principer för beslutsfattande kring tillgänglighet. Avhandlingen är en sammanläggningsavhandling med fem artiklar. Artikel 1 innehåller ett konceptuellt ramverk för beslutsfattande kring IT-tjänsters tillgänglighet som understryker vikten av variansen hos nertidskostnaderna. Artikel 2 visar hur ramverk för organisationsövergripande arkitektur (s.k. enterprise architecture -- EA) kan utvidgas med felträdsanalys (FTA) och bayesianska nätverk (BN) för analys av beroenden mellan komponenter. FTA och BN är bägge etablerade metoder för tillförlitlighets- och tillgänglighetsmodellering. Artikel 3 beskriver en bayesiansk prediktionsmodell för systemtillgänglighet, baserad på utlåtanden från 50 experter. Artikel 4 kombinerar FTA med modelleringselement från EA-ramverket ArchiMate till en metod för tillgänglighetsanalys på verksamhetsnivå. Metoden har validerats i fem fallstudier, där de estimerade årliga nertiderna alltid låg inom åtta timmar från de faktiska värdena. Artikel 5 utvidgar den bayesianska prediktionsmodellen från artikel 3 och modelleringsmetoden från artikel 4 till ett fullständigt EA-ramverk som uttrycks i en probabilistisk version av Object Constraint Language (OCL). Det resulterande modelleringsramverket har testats i nio fallstudier på verksamhetsstödjande IT-system. / <p>QC 20120912</p>