21,271 research outputs found

    Bayesian-network-based fall risk evaluation of steel construction projects by fault tree transformation

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    A fall (also referred to as a tumble) is the most common type of accident at steel construction (SC) sites. To reduce the risk of falls, current site safety management relies mainly on checklist evaluations. However, current onsite inspection is conducted under passive supervision, which fails to provide early warning to occupational accidents. To overcome the limitations of the traditional approach, this paper presents the development of a fall risk assessment model for SC projects by establishing a Bayesian network (BN) based on fault tree (FT) transformation. The model can enhance site safety management through an improved understanding of the probability of fall risks obtained from the analysis of the causes of falls and their relationships in the BN. In practice, based on the analysis of fall risks and safety factors, proper preventive safety management strategies can be established to reduce the occurrences of fall accidents at SC sites

    A scientometric analysis and review of fall from height research in construction

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    Fall from height (FFH) in the construction industry has earned much attention among researchers in recent years. The present review-based study introduced a science mapping approach to evaluate the FFH studies related to the construction industry. This study, through an extensive bibliometric and scientometric assessment, recognized the most active journals, keywords and the nations in the field of FFH studies since 2000. Analysis of the authors’ keywords revealed the emerging research topics in the FFH research community. Recent studies have been discovered to pay more attention to the application of Computer and Information Technology (CIT) tools, particularly building information modelling (BIM) in research related to FFH. Other emerging research areas in the domain of FFH include rule checking, and prevention through design. The findings summarized the mainstream research areas (e.g., safety management program), discussed existing research gaps in FFH domain (e.g., the adaptability of safety management system), and suggests future directions in FFH research. The recommended future directions could contribute to improving safety for the FFH research community by evaluating existing fall prevention programs in different contexts; integrating multiple CIT tools in the entire project lifecycle; designing fall safety courses to workers associated with temporary agents and prototype safety knowledge tool development. The current study was restricted to the FFH literature sample included the journal articles published only in English and in Scopus

    Comment: Expert Elicitation for Reliable System Design

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    Comment: Expert Elicitation for Reliable System Design [arXiv:0708.0279]Comment: Published at http://dx.doi.org/10.1214/088342306000000529 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

    The safety case and the lessons learned for the reliability and maintainability case

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    This paper examine the safety case and the lessons learned for the reliability and maintainability case

    Applying Bayes linear methods to support reliability procurement decisions

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    Bayesian methods are common in reliability and risk assessment, however, such methods often demand a large amount of specification and can be computationally intensive. Because of this, many practitioners are unable to take advantage of many of the benefits found in a Bayesian-based approach. The Bayes linear methodology is similar in spirit to a Bayesian approach but offers an alternative method of making inferences. Bayes linear methods are based on the use of expected values rather than probabilities, and updating is carried out by linear adjustment rather than by Bayes Theorem. The foundations of the method are very strong, based as they are in work of De Finetti and developed further by Goldstein. A Bayes linear model requires less specification than a corresponding probability model and for a given amount of model building effort, one can model a more complex situation quicker. The Bayes linear methodology has the potential to allow us to build ''broad-brush' models that enable us, for example, to explore different test setups or analysis methods and assess the benefits that they can give. The output a Bayes linear model is viewed as an approximation to 'traditional' probabilistic models. The methodology has been applied to support reliability decision making within a current United Kingdom Ministry of Defence (MOD) procurement project. The reliability decision maker had to assess different contractor bids and assess the reliability merit of each bid. Currently the MOD assess reliability programmes subjectively using expert knowledge - for a number of reasons, a quantitative method of assessment in some projects is desirable. The Bayes linear methodology was used to support the decision maker in quantifying his assessment of the reliability of each contractor's bid and determining the effectiveness of each contractor's reliability programme. From this, the decision maker was able to communicate to the project leader and contractors, why a specific contractor was chosen. The methodology has been used in other MOD projects and is considered by those within the MOD as a useful tool to support decision making. The paper will contain the following. The paper will introduce the Bayes linear methodology and briefly discuss some of the philosophical implications of adopting a Bayes linear methodology within the context of a reliability programme analysis. The paper will briefly introduce the reliability domain and the reasons why it is believed that the Bayes linear methodology can offer support to decision makers. An in-depth analysis of the problem will then be given documenting the steps taken in the project and how future decision makers can apply the methodology. A brief summary will then be given as to possible future work for those interested in the Bayes linear methodology

    A novel planning approach for the water, sanitation and hygiene (WaSH) sector: the use of object-oriented bayesian networks

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    Conventional approaches to design and plan water, sanitation, and hygiene (WaSH) interventions are not suitable for capturing the increasing complexity of the context in which these services are delivered. Multidimensional tools are needed to unravel the links between access to basic services and the socio-economic drivers of poverty. This paper applies an object-oriented Bayesian network to reflect the main issues that determine access to WaSH services. A national Program in Kenya has been analyzed as initial case study. The main findings suggest that the proposed approach is able to accommodate local conditions and to represent an accurate reflection of the complexities of WaSH issues, incorporating the uncertainty intrinsic to service delivery processes. Results indicate those areas in which policy makers should prioritize efforts and resources. Similarly, the study shows the effects of sector interventions, as well as the foreseen impact of various scenarios related to the national Program.Preprin

    A hybrid and integrated approach to evaluate and prevent disasters

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    Expert Elicitation for Reliable System Design

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    This paper reviews the role of expert judgement to support reliability assessments within the systems engineering design process. Generic design processes are described to give the context and a discussion is given about the nature of the reliability assessments required in the different systems engineering phases. It is argued that, as far as meeting reliability requirements is concerned, the whole design process is more akin to a statistical control process than to a straightforward statistical problem of assessing an unknown distribution. This leads to features of the expert judgement problem in the design context which are substantially different from those seen, for example, in risk assessment. In particular, the role of experts in problem structuring and in developing failure mitigation options is much more prominent, and there is a need to take into account the reliability potential for future mitigation measures downstream in the system life cycle. An overview is given of the stakeholders typically involved in large scale systems engineering design projects, and this is used to argue the need for methods that expose potential judgemental biases in order to generate analyses that can be said to provide rational consensus about uncertainties. Finally, a number of key points are developed with the aim of moving toward a framework that provides a holistic method for tracking reliability assessment through the design process.Comment: This paper commented in: [arXiv:0708.0285], [arXiv:0708.0287], [arXiv:0708.0288]. Rejoinder in [arXiv:0708.0293]. Published at http://dx.doi.org/10.1214/088342306000000510 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org
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