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Intelligent laser micromachining parameter optimization via causality-enhanced data-driven modeling
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DOI：10.1016/j.jmapro.2026.02.003.png)
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Abstract
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• Constructing a dataset for the laser machining process. • Establishing a process surrogate model using a causality-enhanced neural network. • The process optimization results were validated through physical experiments.
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