894 resultados para Risk based Maintenance


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In dynamic and uncertain environments, where the needs of security and information availability are difficult to balance, an access control approach based on a static policy will be suboptimal regardless of how comprehensive it is. Risk-based approaches to access control attempt to address this problem by allocating a limited budget to users, through which they pay for the exceptions deemed necessary. So far the primary focus has been on how to incorporate the notion of budget into access control rather than what or if there is an optimal amount of budget to allocate to users. In this paper we discuss the problems that arise from a sub-optimal allocation of budget and introduce a generalised characterisation of an optimal budget allocation function that maximises organisations expected benefit in the presence of self-interested employees and costly audit.

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Airports worldwide represent key forms of critical infrastructure in addition to serving as nodes in the international aviation network. While the continued operation of airports is critical to the functioning of reliable air passenger and freight transportation, these infrastructure systems face a number of sources of disturbance that threaten their operational viability. Recent examples of high magnitude events include the eruption of Iceland’s Eyjafjallajokull volcano eruption (Folattau and Schofield 2010), the failure of multiple systems at the opening of Heathrow’s Terminal 5 (Brady and Davies 2010) and the Glasgow airport 2007 terrorist attack (Crichton 2008). While these newsworthy events do occur, a multitude of lower-level more common disturbances also have the potential to cause significant discontinuity to airport operations. Regional airports face a unique set of challenges, particularly in a nation like Australia where they serve to link otherwise remote and isolated communities to metropolitan hubs (Wheeler 2005), often without the resources and political attention received by larger capital city airports. This paper discusses conceptual relationships between Business Continuity Management (BCM) and High Reliability Theory, and proposes BCM as an appropriate risk-based management process to ensure continued airport operation in the face of uncertainty. In addition, it argues that that correctly implemented BCM can lead to highly reliable organisations. This is framed within the broader context of critical infrastructures and the need for adequate crisis management approaches suited to their unique requirements (Boin and McConnell 2007).

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The ability to accurately predict the remaining useful life of machine components is critical for machine continuous operation, and can also improve productivity and enhance system safety. In condition-based maintenance (CBM), maintenance is performed based on information collected through condition monitoring and an assessment of the machine health. Effective diagnostics and prognostics are important aspects of CBM for maintenance engineers to schedule a repair and to acquire replacement components before the components actually fail. All machine components are subjected to degradation processes in real environments and they have certain failure characteristics which can be related to the operating conditions. This paper describes a technique for accurate assessment of the remnant life of machines based on health state probability estimation and involving historical knowledge embedded in the closed loop diagnostics and prognostics systems. The technique uses a Support Vector Machine (SVM) classifier as a tool for estimating health state probability of machine degradation, which can affect the accuracy of prediction. To validate the feasibility of the proposed model, real life historical data from bearings of High Pressure Liquefied Natural Gas (HP-LNG) pumps were analysed and used to obtain the optimal prediction of remaining useful life. The results obtained were very encouraging and showed that the proposed prognostic system based on health state probability estimation has the potential to be used as an estimation tool for remnant life prediction in industrial machinery.

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In condition-based maintenance (CBM), effective diagnostic and prognostic tools are essential for maintenance engineers to identify imminent fault and predict the remaining useful life before the components finally fail. This enables remedial actions to be taken in advance and reschedule of production if necessary. All machine components are subjected to degradation processes in real environments and they have certain failure characteristics which can be related to the operating conditions. This paper describes a technique for accurate assessment of the remnant life of bearings based on health state probability estimation and historical knowledge embedded in the closed loop diagnostics and prognostics system. The technique uses the Support Vector Machine (SVM) classifier as a tool for estimating health state probability of machine degradation process to provide long term prediction. To validate the feasibility of the proposed model, real life fault historical data from bearings of High Pressure-Liquefied Natural Gas (HP-LNG) pumps were analysed and used to obtain the optimal prediction of remaining useful life (RUL). The results obtained were very encouraging and showed that the proposed prognosis system based on health state probability estimation has the potential to be used as an estimation tool for remnant life prediction in industrial machinery.

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Introduction Risk factor analyses for nosocomial infections (NIs) are complex. First, due to competing events for NI, the association between risk factors of NI as measured using hazard rates may not coincide with the association using cumulative probability (risk). Second, patients from the same intensive care unit (ICU) who share the same environmental exposure are likely to be more similar with regard to risk factors predisposing to a NI than patients from different ICUs. We aimed to develop an analytical approach to account for both features and to use it to evaluate associations between patient- and ICU-level characteristics with both rates of NI and competing risks and with the cumulative probability of infection. Methods We considered a multicenter database of 159 intensive care units containing 109,216 admissions (813,739 admission-days) from the Spanish HELICS-ENVIN ICU network. We analyzed the data using two models: an etiologic model (rate based) and a predictive model (risk based). In both models, random effects (shared frailties) were introduced to assess heterogeneity. Death and discharge without NI are treated as competing events for NI. Results There was a large heterogeneity across ICUs in NI hazard rates, which remained after accounting for multilevel risk factors, meaning that there are remaining unobserved ICU-specific factors that influence NI occurrence. Heterogeneity across ICUs in terms of cumulative probability of NI was even more pronounced. Several risk factors had markedly different associations in the rate-based and risk-based models. For some, the associations differed in magnitude. For example, high Acute Physiology and Chronic Health Evaluation II (APACHE II) scores were associated with modest increases in the rate of nosocomial bacteremia, but large increases in the risk. Others differed in sign, for example respiratory vs cardiovascular diagnostic categories were associated with a reduced rate of nosocomial bacteremia, but an increased risk. Conclusions A combination of competing risks and multilevel models is required to understand direct and indirect risk factors for NI and distinguish patient-level from ICU-level factors.

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The ability to estimate the expected Remaining Useful Life (RUL) is critical to reduce maintenance costs, operational downtime and safety hazards. In most industries, reliability analysis is based on the Reliability Centred Maintenance (RCM) and lifetime distribution models. In these models, the lifetime of an asset is estimated using failure time data; however, statistically sufficient failure time data are often difficult to attain in practice due to the fixed time-based replacement and the small population of identical assets. When condition indicator data are available in addition to failure time data, one of the alternate approaches to the traditional reliability models is the Condition-Based Maintenance (CBM). The covariate-based hazard modelling is one of CBM approaches. There are a number of covariate-based hazard models; however, little study has been conducted to evaluate the performance of these models in asset life prediction using various condition indicators and data availability. This paper reviews two covariate-based hazard models, Proportional Hazard Model (PHM) and Proportional Covariate Model (PCM). To assess these models’ performance, the expected RUL is compared to the actual RUL. Outcomes demonstrate that both models achieve convincingly good results in RUL prediction; however, PCM has smaller absolute prediction error. In addition, PHM shows over-smoothing tendency compared to PCM in sudden changes of condition data. Moreover, the case studies show PCM is not being biased in the case of small sample size.

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Anthelmintic drugs are widely used to control parasitic infections in cattle. The ProSafeBeef project addressed the need for data on the exposure of European consumers of beef to potentially harmful drug residues. A novel analytical method based on matrix solid-phase dispersive extraction and ultra-performance liquid chromatography-tandem mass spectrometry was validated for 37 anthelmintic drugs and metabolites in muscle (assay decision limits, CCa, = 0.15-10.2 µg kg -1). Seven European countries (France, Spain, Slovenia, Ireland, Italy, Belgium and Portugal) participated in a survey of retail beef purchased in local shops. Of 1061 beef samples analysed, 26 (2.45%) contained detectable residues of anthelmintic drugs (0.2-171 µg kg -1), none above its European Union maximum residue limit (MRL) or action level. Residues detected included closantel, levamisole, doramectin, eprinomectin, moxidectin, ivermectin, albendazole and rafoxanide. In a risk assessment applied to mean residue concentrations across all samples, observed residues accounted for less than 0.1% of the MRL for each compound. An exposure assessment based on the consumption of meat at the 99th percentile of consumption of adults in 14 European countries demonstrated that beef accounted for less than 0.02% of the acceptable daily intake for each compound in each country. This study is the first of its kind to apply such a risk-based approach to an extensive multi-residue survey of veterinary drug residues in food. It has demonstrated that the risk of exposure of the European consumer to anthelmintic drug residues in beef is negligible, indicating that regulation and monitoring is having the desired effect of limiting residues to non-hazardous concentrations. © 2012 Copyright Taylor and Francis Group, LLC.

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Risk management in software engineering has become a recognized project management practice but it seems that not all companies are systematically applying it. At the same time, agile methods have become popular, partly because proponents claim that agile methods implicitly reduce risks due
to, for example, more frequent and earlier feedback, shorter periods of development time and easier prediction of cost. Therefore, there is a need to investigate how risk management can be usable in iterative and evolutionary software development processes. This paper investigates the gathering of empirical data on risk management from the project environment and presents
a novel approach to manage risk in agile projects. Our approach is based on a prototype tool, Agile Risk Tool (ART). This tool reduces human effort in risk management by using software agents to identify, assess and monitor risk, based on input and data collected from the project environment and by applying
some designated rules. As validation, groups of student project data were used to provide evidence of the efficacy of this approach. We demonstrate the approach and the feasibility of using a lightweight risk management tool to alert, assess and monitor risk with reduced human effort.

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Media reporting of and public concern about sexual offending, particularly relating to children, affects and reflects political, policy and organisational responses to those convicted of such crimes. The development of regulatory policies on sexual offending has taken place within a highly emotive and overtly politicized public and policy discourse. This chapter charts the various ways in which the risks imagined or posed by sexual offenders have been conceptualised within public discourses and regulated and managed under the legislative and organisational ‘risk paradigm.’ Ultimately, it argues that risk-based responses to sexual offending are at best uncertain in their effects and at worst counterproductive, in that they often reduce the potential for successful reintegration. In seeking to look ‘beyond risk’, the chapter also explores the usefulness of restorative and related practices in supporting sex offender reintegration aimed at the primary and secondary levels of harm prevention.

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To evaluate how young physicians in training perceive their patients' cardiovascular risk based on the medical charts and their clinical judgment. Cross sectional observational study. University outpatient clinic, Lausanne, Switzerland. Two hundred hypertensive patients and 50 non-hypertensive patients with at least one cardiovascular risk factor. Comparison of the absolute 10-year cardiovascular risk calculated by a computer program based on the Framingham score and adapted for physicians by the WHO/ISH with the perceived risk as assessed clinically by the physicians. Physicians underestimated the 10-year cardiovascular risk of their patients compared to that calculated with the Framingham score. Concordance between methods was 39% for hypertensive patients and 30% for non-hypertensive patients. Underestimation of cardiovascular risks for hypertensive patients was related to the fact they had a stabilized systolic blood pressure under 140 mm Hg (OR = 2.1 [1.1; 4.1]). These data show that young physicians in training often have an incorrect perception of the cardiovascular risk of their patients with a tendency to underestimate the risk. However, the calculated risk could also be slightly overestimated when applying the Framingham Heart Study model to a Swiss population. To implement a systematic evaluation of risk factors in primary care a greater emphasis should be placed on the teaching of cardiovascular risk evaluation and on the implementation of quality improvement programs.

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The primary objective of this non-experimental study was to examine the differences based on obesity-related health risk in terms of physical activity, sedentary behaviour and well-being in adults. Participants (N = 50; Mage = 38.50, SDage = 14.21) were asked to wear a SenseWear Armband (SWA) across a seven day monitoring period followed by a questionnaire package. Using the National Institute of Health’s (1998) criteria, participants were classified as either least, increased, or high risk based on waist circumference and Body Mass Index scores. Differences between these classifications were found in the amount of time spent in active energy expenditure for bouts of ten minutes or more (p = .002); specifically between least and high risk (p < .05). No other differences (p > .05) emerged. Participants’ also perceived the SWA as a practical and worthwhile device. Overall, these findings provide practical applications and future directions for health promotional research.

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Refiners today operate their equipment for prolonged periods without shutdown. This is primarily due to the increased pressures of the market resulting in extended shutdown-to-shutdown intervals. This places extreme demands on the reliability of the plant equipment. The traditional methods of reliability assurance, like Preventive Maintenance, Predictive Maintenance and Condition Based Maintenance become inadequate in the face of such demands. The alternate approaches to reliability improvement, being adopted the world over are implementation of RCFA programs and Reliability Centered Maintenance. However refiners and process plants find it difficult to adopt this standardized methodology of RCM mainly due to the complexity and the large amount of analysis that needs to be done, resulting in a long drawn out implementation, requiring the services of a number of skilled people. These results in either an implementation restricted to only few equipment or alternately, one that is non-standard. The paper presents the current models in use, the core requirements of a standard RCM model, the alternatives to classical RCM, limitations in the existing model, classical RCM and available alternatives to RCM and will then go on to present an ‗Accelerated‘ approach to RCM implementation, that, while ensuring close conformance to the standard, does not place a large burden on the implementers

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This paper presents an assessment of the implications of climate change for global river flood risk. It is based on the estimation of flood frequency relationships at a grid resolution of 0.5 × 0.5°, using a global hydrological model with climate scenarios derived from 21 climate models, together with projections of future population. Four indicators of the flood hazard are calculated; change in the magnitude and return period of flood peaks, flood-prone population and cropland exposed to substantial change in flood frequency, and a generalised measure of regional flood risk based on combining frequency curves with generic flood damage functions. Under one climate model, emissions and socioeconomic scenario (HadCM3 and SRES A1b), in 2050 the current 100-year flood would occur at least twice as frequently across 40 % of the globe, approximately 450 million flood-prone people and 430 thousand km2 of flood-prone cropland would be exposed to a doubling of flood frequency, and global flood risk would increase by approximately 187 % over the risk in 2050 in the absence of climate change. There is strong regional variability (most adverse impacts would be in Asia), and considerable variability between climate models. In 2050, the range in increased exposure across 21 climate models under SRES A1b is 31–450 million people and 59 to 430 thousand km2 of cropland, and the change in risk varies between −9 and +376 %. The paper presents impacts by region, and also presents relationships between change in global mean surface temperature and impacts on the global flood hazard. There are a number of caveats with the analysis; it is based on one global hydrological model only, the climate scenarios are constructed using pattern-scaling, and the precise impacts are sensitive to some of the assumptions in the definition and application.

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With the change of the water environment in accordance with climate change, the loss of lives and properties has increased due to urban flood. Although the importance of urban floods has been highlighted quickly, the construction of advancement technology of an urban drainage system combined with inland-river water and its relevant research has not been emphasized in Korea. In addition, without operation in consideration of combined inland-river water, it is difficult to prevent urban flooding effectively. This study, therefore, develops the uncertainty quantification technology of the risk-based water level and the assessment technology of a flood-risk region through a flooding analysis of the combination of inland-river. The study is also conducted to develop forecast technology of change in the water level of an urban region through the construction of very short-term/short-term flood forecast systems. This study is expected to be able to build an urban flood forecast system which makes it possible to support decision making for systematic disaster prevention which can cope actively with climate change.

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O objetivo principal deste trabalho é avaliar as formas de contratação de manutenção industrial praticadas nos últimos anos e identificar os elementos que devem ser considerados na elaboração de um contrato baseado em performance, com remuneração variável e cláusulas de risco, sob a óptica de quem contrata (indústrias) e de quem fornece (empresas especializadas) esse tipo de serviço. Para se chegar ao modelo sugerido, o estudo utiliza uma analogia com o "jogo da forca" (jogo infantil de salão que baseia-se no processo de tentativa e erro) para desenvolver um processo de desconstrução dos modelos atuais de contratação de manutenção, identificando os fatores determinantes (para cada forma de contrato mais utilizada) para o insucesso financeiro e operacional atualmente percebido. Após a tentativa de ordenação das causas dos problemas correntes, o trabalho passa para o objetivo principal, que é o de listar os fatores críticos de sucesso para um contrato de manutenção por performance e, finalmente, sugerir um modelo básico de atuação para que os resultados almejados sejam obtidos. Com a identificação e implementação desses elementos num novo modelo de contrato de risco de manutenção, acredita-se ser possível minimizar os problemas comerciais e operacionais que atualmente representam obstáculos ao sucesso da terceirização da manutenção em plantas industriais, particularmente no Brasil . A metodologia se baseia em análise dos resultados de pesquisa de campo através de questionário realizado junto aos principais gestores de grandes grupos industriais e com os executivos das empresas prestadoras de serviço de manutenção industrial.