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In this paper, we present both a failure model for voting architectures based on Bayesian networks and a maintenance model based on continuous time Markov chains, and we propose to combine them according to a compositional multiformalism modeling approach in order to analyze the impact of imperfect maintenance on the system safety.
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However, current condition-based maintenance (CBM) models based on component health indices are not suitable for degraded control systems.
Further research on the limitations, maintenance and implementation costs of model based controllers in this application would be worthwhile.
Our results are consistent with a "positive only" model (based on a different line of experimentation) for maintenance of pluripotency of ESCs (Chamberlain et al., 2008).
However, a decision model based on decision trees exponentially grows with inspection and maintenance number.
To estimate minor and major maintenance operations of BSB scenario in comparison to traditional ballasted track-bed, an integrated model, based on laboratory tests, combining the evolution of track irregularities and ballast contamination with traffic, was used.
In this paper, we propose a quantitative model based on measurable physiological parameters and the concept of energy tradeoffs between biomass synthesis and maintenance for endothermic animals.
Develop a model based on theory.
There are four maintenance strategies (html and February 2014): reactive maintenance, which allows the machine to run until failure, periodic preventive maintenance, preventive maintenance based on inspections, maintenance based on remote monitoring of parameters describing the condition of the device.
reactive maintenance, which allows the machine to run until failure, periodic preventive maintenance, preventive maintenance based on inspections, maintenance based on remote monitoring of parameters describing the condition of the device.
We present two dual control approaches to the model maintenance problem based on adaptive model predictive control (mpc).
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