System reliability and weighted lattice polynomials

The lifetime of a system of connected units under some natural assumptions can be represented as a random variable Y defined as a weighted lattice polynomial of random lifetimes of its components. As such, the concept of a random variable Y defined by a weighted lattice polynomial of (lattice-valued) random variables is considered in general and in some special cases. The central object of interest is the cumulative distribution function of Y. In particular, numerous results are obtained for lattice polynomials and weighted lattice polynomials in case of independent arguments and in general. For the general case, the technique consists in considering the joint probability generating function of "indicator" variables. A connection is studied between Y and order statistics of the set of arguments.Comment: Revised version (minor changes

Reliability of systems with dependent components based on lattice polynomial description

Reliability of a system is considered where the components' random lifetimes may be dependent. The structure of the system is described by an associated "lattice polynomial" function. Based on that descriptor, general framework formulas are developed and used to obtain direct results for the cases where a) the lifetimes are "Bayes-dependent", that is, their interdependence is due to external factors (in particular, where the factor is the "preliminary phase" duration) and b) where the lifetimes' dependence is implied by upper or lower bounds on lifetimes of components in some subsets of the system. (The bounds may be imposed externally based, say, on the connections environment.) Several special cases are investigated in detail

Maintenance Scheduling in Power Electronic Converters Considering Wear-out Failures

Power electronic converters are one of failure sources in energy systems, and hence drivers of downtime costs in power systems. Different approaches can be employed for converter reliability enhancement including design/control for reliability methods, condition monitoring and fault diagnosis, and maintenance strategies. This paper proposes optimal preventive maintenance strategies based on wear-out failure model of converter components. The proposed approaches employ two different performance measures at converter-level and system-level. The converter-level measures take into account planned and unplanned maintenance times or costs in a single unit or small-scale system. Moreover, the system-level measure considers not only maintenance times, but also energy losses and additional maintenance costs induced by aging of the converter components. The outcome is optimal replacement time of converter and its components, which depends on the employed performance measure. Optimal replacement scheduling is of importance for risk management and decision-making during planning of modern power electronic based power systems. The applicability of the proposed approaches is illustrated by numerical analysis in a photovoltaic system

Function Modelling using the System State Flow Diagram

yesThis paper introduces a rigorous framework for function modelling of complex multi-disciplinary systems based on the System State Flow Diagram (SSFD). The work addresses the need for a consistent methodology to support solution neutral function based system decomposition analysis, facilitating the design, modelling and analysis of complex systems architectures. A rigorous basis for the SSFD is established by defining conventions for states and function definition and representation scheme, underpinned by a critical review of existing literature. A set of heuristics are introduced to support the function decomposition analysis and to facilitate the deployment of the methodology with strong practitioner guidelines. The SSFD heuristics extend the existing framework of Otto and Wood (2001) by introducing a conditional fork node heuristic, to facilitate analysis and aggregation of function models across multiple modes of operation of the system. The empirical validation of the SSFD function modelling framework is discussed in relation to its application to two case studies: (i) a benchmark problem (Glue Gun) set for the engineering design community; and (ii) an industrial case study of an electric vehicle powertrain. Based on the evidence from the two case studies presented in the paper, a critical evaluation of the SSFD function modelling methodology is presented based on the function benchmarking framework established by Summers et al (2013), considering the representation, modelling, cognitive and reasoning characteristics. The significance of this paper is that it establishes a rigorous reference framework for the SSFD function representation and a consistent methodology to guide the practitioner with its deployment, facilitating its impact to industrial practice

Aplicação de um modelo de riscos concorrentes na análise de confiabilidade de dados de garantia

Em análise de confiabilidade, espera-se que dados de vida de equipamentos sigam uma distribuição de probabilidade conhecida, como, por exemplo, uma distribuição de Weibull ou Lognormal. Entretanto, quando se modelam falhas originadas em campo, essas podem decorrer de causas múltiplas e os tempos-até-falha podem, assim, estar associados a diferentes estágios do ciclo de vida de um produto, não se ajustando a uma distribuição de probabilidade única. Neste artigo, propõe-se a utilização de um modelo misto que possa ser aplicado na análise de dados de vida oriundos de duas fases do ciclo de vida de um produto: a fase de vida operacional e a fase de envelhecimento (desgaste). O modelo proposto combina elementos de uma distribuição exponencial e de uma distribuição de Weibull com dois parâmetros. Equações de confiabilidade e estimadores de máxima verossimilhança são empregados para definir os parâmetros do modelo e para ilustrar os desenvolvimentos propostos. Um teste de ajuste é utilizado para verificar o desempenho do modelo sugerido

Addressing failure rate uncertainties of marine energy converters

publication-status: Publishedtypes: ArticleThe interest in marine renewable energy is strong, but has not led to significant commercial-scale investment and deployment, yet. To attract investors and promote the development of a marine renewable industry a clear concept of project risk is paramount, in particular issues relating to device reliability are critical. In the public domain, reliability information is often scarce or inappropriate at this early stage of development, as little operational experience has been gained. Thus, reliability estimates are fraught with large uncertainties. This paper explores sources and magnitudes of failure rate uncertainty and demonstrates the effect on reliability estimates for a notional marine energy converter. If generic failure rate data forms the basis of a reliability assessment, reliability estimates are not robust and may significantly over- or underestimate system reliability. The Bayesian statistical framework provides a method to overcome this issue. Generic data can be updated with more specific information that could not be statistically incorporated otherwise. It is proposed that adopting such an approach at an early stage in an iterative process will lead to an improved rate of certainty

Reliability and Availability Evaluation of Wireless Sensor Networks for Industrial Applications

Wireless Sensor Networks (WSN) currently represent the best candidate to be adopted as the communication solution for the last mile connection in process control and monitoring applications in industrial environments. Most of these applications have stringent dependability (reliability and availability) requirements, as a system failure may result in economic losses, put people in danger or lead to environmental damages. Among the different type of faults that can lead to a system failure, permanent faults on network devices have a major impact. They can hamper communications over long periods of time and consequently disturb, or even disable, control algorithms. The lack of a structured approach enabling the evaluation of permanent faults, prevents system designers to optimize decisions that minimize these occurrences. In this work we propose a methodology based on an automatic generation of a fault tree to evaluate the reliability and availability of Wireless Sensor Networks, when permanent faults occur on network devices. The proposal supports any topology, different levels of redundancy, network reconfigurations, criticality of devices and arbitrary failure conditions. The proposed methodology is particularly suitable for the design and validation of Wireless Sensor Networks when trying to optimize its reliability and availability requirements

Modelling the probability of microhabitat formation on trees using cross-sectional data

The rate of TreM formation per unit diameter growth was modelled as a function of tree diameter at breast height (DBH), and the model was calibrated considering cross-sectional observations TreMs on trees of different sizes. The model predicted realistic TreM formation rates at the tree and stand levels in forests dominated by Abies alba and Fagus sylvatica. This approach opens new perspectives to the analysis of forest biodiversity conservation strategies

Assessment of performance indices of selected gas turbine power plants in Nigeria

In this study, performance assessment of selected gas turbine power plants in Nigeria was evaluated using performance indices. The results of the study showed that for the period under review (2006–2010), the percentage shortfalls from the target energy in the selected power plants range from 26.33% to 86.61% as against the acceptable value of 5–10%. The capacity factor of the selected power plants varies from 16.88% to 73.67% as against the international value of 50–80%. The plant use factor varies from 45.89% to 97.03% and the utilization factor varies from 6.31% to 93.074% as against the international best practice of over 95%. From this result, it can be concluded that the generating units were underutilized. This is due to inadequate routine maintenance and equipment fault development. The analyses of reliability indicators revealed that the mean time between failures varies from 5.42 to 378.44 h, the mean time to repair varies from 18.3 to 153.88 h and the plant availability varies from 12.86% to 91.31% as against the Institute of Electrical and Electronics Engineers recommended standard of 99.9%. Evaluation of operating figures of the selected power plants revealed that starting reliability (SR) and operating reliability vary from 71.95% to 93.9% and 5.33% to 55%, respectively. The SR of the selected power plants is low in value compared with standard value of 99.9%. The statistical analysis carried out on plant availability revealed that at 95% confidence level; there is a significant difference in availability of the selected power plants. This indicates differences in their systems installation, operation and maintenance. The performance indicator developed to evaluate the performance indices for the selected stations can also be applicable to other power stations in Nigeria and elsewhere. Measures to improve the performance indices of the plants have been suggested in this paper