A system for design decisions based on reliability block diagrams

Gissler, Bob; Shrivastava, Pankaj

doi:10.1109/rams.2015.7105105

Cited by 11 publications

(4 citation statements)

References 3 publications

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“…These values correspond in general to the probability of lack of packet delivery at the levels of 0.01% and 0.001%, respectively. When looking at the pure definition of the term, reliability is the probability specifying that the wireless network operates properly without any device or link failure [ 39 ]. However, these terms should not be confused with availability, which describes the proportion of time when the system is in a functioning condition.…”

Section: Network Reliability Assessment Through the Percolation Thmentioning

confidence: 99%

“…However, these terms should not be confused with availability, which describes the proportion of time when the system is in a functioning condition. Various methods can be used for reliability assessment, e.g., Markov Chains, Fault Trees, or RBD [ 39 ]. However, these approaches do not reflect well or easily the stochastic nature of such dense wireless networks, whose performance strongly depends on the current node distribution and node load.…”

Section: Network Reliability Assessment Through the Percolation Thmentioning

confidence: 99%

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Brain-Inspired Data Transmission in Dense Wireless Network

Kułacz

Kliks

2021

Sensors

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In this paper, the authors investigate the innovative concept of a dense wireless network supported by additional functionalities inspired by the human nervous system. The nervous system controls the entire human body due to reliable and energetically effective signal transmission. Among the structure and modes of operation of such an ultra-dense network of neurons and glial cells, the authors selected the most worthwhile when planning a dense wireless network. These ideas were captured, modeled in the context of wireless data transmission. The performance of such an approach have been analyzed in two ways, first, the theoretic limits of such an approach has been derived based on the stochastic geometry, in particular—based on the percolation theory. Additionally, computer experiments have been carried out to verify the performance of the proposed transmission schemes in four simulation scenarios. Achieved results showed the prospective improvement of the reliability of the wireless networks while applying proposed bio-inspired solutions and keeping the transmission extremely simple.

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Section: Network Reliability Assessment Through the Percolation Thmentioning

confidence: 99%

Section: Network Reliability Assessment Through the Percolation Thmentioning

confidence: 99%

Brain-Inspired Data Transmission in Dense Wireless Network

Kułacz

Kliks

2021

Sensors

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“…25 FTA illustrates all possible combinations of potential failures and events that may cause a specified system failure, and it is a system fault–oriented analysis method, 26,27 and RBD is a success-oriented network illustrating how the functioning of the various functional blocks may ensure that the system function is fulfilled. 28,29 Among the quantitative analysis methods, the Markov process is widely used in the reliability analysis of complex systems due to its flexibility. Based on the Markov method, Liu et al 30 proposed a reliability model for the electrical control system of a subsea blowout preventer stack, and evaluated the reliability of the system.…”

Section: Introductionmentioning

confidence: 99%

Design and reliability analysis of the electrical control system of the subsea control module

Wang

Lizhang

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part I:

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“…Reliability Block Diagrams (RBD) are commonly used for analysis of system reliability [1,2]. These diagrams model how the combinations of system components contribute to the success or failure of systems.…”

Section: Introductionmentioning

confidence: 99%

Reliability block diagram extensions for non-parametric probabilistic analysis

Davis

Thornton

Manikas

2016

2016 Annual IEEE Systems Conference (SysCon)

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Multi-Valued ReliabilityBlock Diagrams (MVRBD) are introduced as a generalization of classical reliability block diagrams (RBD) commonly used in system analysis. MVRBD offer the advantage of allowing systems and subsystem components to be modeled with arbitrary hazard failure rate relationships. MVRBD are based upon a multiplevalued discrete switching algebra that is functionally complete with constants thereby affording a corresponding model to be formulated for any system that is capable of being modeled in a reliability block diagram form. The utility of this new model is that system failure and reliability analysis can be performed without restricting component hazard rate relationships to the binary case of either "failure" or "fully operational." The incorporation of any desired number of "degraded" states into the MVRBD model allows for non-parametric probability mass functions (pmf) to be used.Any arbitrary number of intermediate system states of "degraded" may be incorporated into the MVRBD model without significant increase in the complexity of the analyses methodologies.

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A system for design decisions based on reliability block diagrams

Cited by 11 publications

References 3 publications

Brain-Inspired Data Transmission in Dense Wireless Network

Brain-Inspired Data Transmission in Dense Wireless Network

Design and reliability analysis of the electrical control system of the subsea control module

Reliability block diagram extensions for non-parametric probabilistic analysis

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