A simplified approach for reliability evaluation and component allocation in three-state series and parallel systems composed of non-identical components
“…In general, system reliability (R s ) is understood as the probability that the system will operate continuously throughout its useful life [9]. The total reliability of a system depends on both the reliability of all its components and the way they are arranged [3]. Serial arrangement (Fig.…”
Section: Problems Of Designing Rms Production Structuresmentioning
Article citation info: (*) Tekst artykułu w polskiej wersji językowej dostępny w elektronicznym wydaniu kwartalnika na stronie www.ein.org.pl GolA A. Reliability analysis of reconfigurable manufacturing system structures using computer simulation methods. Eksploatacja i
“…In general, system reliability (R s ) is understood as the probability that the system will operate continuously throughout its useful life [9]. The total reliability of a system depends on both the reliability of all its components and the way they are arranged [3]. Serial arrangement (Fig.…”
Section: Problems Of Designing Rms Production Structuresmentioning
Article citation info: (*) Tekst artykułu w polskiej wersji językowej dostępny w elektronicznym wydaniu kwartalnika na stronie www.ein.org.pl GolA A. Reliability analysis of reconfigurable manufacturing system structures using computer simulation methods. Eksploatacja i
“…Estudos futuros podem gerar formulações voltadas à otimização da efi ciência global da máquina, medida pelo IROG. A otimização de crono gramas de manutenção em sistemas multiestado, onde componentes podem falhar em múltiplos modos (ANZANELLO, 2009), também constitui-se em possível desdobramento.…”
Este artigo propõe um método para otimização do cronograma de manutenção preventiva com vistas à minimização dos custos associados. Dados de falhas são coletados e modelados através de distribuições de probabilidades paramétricas. Na sequência, geram-se índices de melhoria associados aos incrementos de confiabilidade decorrentes das manutenções, valendo-se do conhecimento de especialistas de processo, conforme Tsai et al. (2001). Tais índices são integrados a formulações quantificadoras do custo incorrido pelos procedimentos de manutenção. A formulação é otimizada através de Algoritmo Genético (AG), determinando o melhor tipo de manutenção (por exemplo, manutenção total ou parcial) a ser realizada em intervalos pré-definidos. Ao ser aplicado em uma máquina de transformação de bobinas de aço plano em tubos, o método gerou um cronograma coerente de manutenções com base na avaliação de especialistas de processo, além de reduzir em 20% os custos comparados à programação empírica de manutenção. Os resultados ainda comprovam a eficiência de AGs na resolução de problemas de manutenção por conta de sua rápida convergência e fácil implementação.
“…The binary k-out-of-n system reliability models have been extended to multi-state k-out-of-n system reliability models by allowing more than two performance levels for the system and its components (Eryilmaz 2014). Multi-state systems contain units presenting two or more failed states with multiple modes of failure and one working state (Anzanello 2009). Reliability models provide, through multistate, more realistic representations of engineering systems (Yingkui & Jing 2012).…”
In this paper, we introduce a new two-parameter lifetime distribution, called the exponential-generalized truncated logarithmic (EGTL) distribution, by compounding the exponential and generalized truncated logarithmic distributions. Our procedure generalizes the exponential-logarithmic (EL) distribution modelling the reliability of systems by the use of first-order concepts, where the minimum lifetime is considered (Tahmasbi & Rezaei 2008). In our approach, we assume that a system fails if a given number k of the components fails and then, we consider the k th -smallest value of lifetime instead of the minimum lifetime. The reliability and failure rate functions as well as their properties are presented for some special cases. The estimation of the parameters is attained by the maximum likelihood, the expectation maximization algorithm, the method of moments and the Bayesian approach, with a simulation study performed to illustrate the different methods of estimation. The application study is illustrated based on two real data sets used in many applications of reliability.
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