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In this paper we study how supervised machine learning could be applied to build simplified models of realtime (RT) reliability management response to the realization of uncertainties. The final objective is to import these models into look-ahead operation planning under uncertainties. Our response models predict in particular the real-time reliability management costs and the resulting reliability...
Power system states are not accurately known ahead of real time and are subject to natural variability, which leads to uncertainty in the system. Sources of uncertainty are amongst others load, renewable energy sources and contingencies. An aggregate measure for system's uncertainty is determined in order to have a single quantified value of the uncertainty level in the system. This allows to compare...
In response to the shortening product life cycle, we have increased parallelism in all aspects of our work in the microelectronics industry. In order to produce an integrated solution, management has increased the emphasis on teams. As an example, building-in reliability (BIR) during new product development and manufacturing in the semiconductor industry requires teams of technologists from design,...
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