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- W4296558753 abstract "We propose a framework for the configuration and operation of expensive-to-evaluate advanced manufacturing methods, based on Bayesian optimization. The framework unifies a tailored acquisition function, a parallel acquisition procedure, and the integration of process information providing context to the optimization procedure. cmtb{The novel acquisition function is demonstrated, analyzed and compared on state-of-the-art benchmarking problems. We apply the optimization approach to atmospheric plasma spraying and fused deposition modeling.} Our results demonstrate that the proposed framework can efficiently find input parameters that produce the desired outcome and minimize the process cost." @default.
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- W4296558753 date "2022-10-01" @default.
- W4296558753 modified "2023-10-16" @default.
- W4296558753 title "Advanced Manufacturing Configuration by Sample-Efficient Batch Bayesian Optimization" @default.
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- W4296558753 doi "https://doi.org/10.1109/lra.2022.3208370" @default.
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