Proceedings of JSPE Semestrial Meeting
2023 JSPE Autumn Conference
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Development of a Performance Prediction Method for Machined Hole Features Toward the Application of Digital Twin to Laser Via Hole Machining
*Soma NowatariToshiki HirogakiEiichi Aoyama
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Keywords: Machine Learning, Lazer
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Pages 175-176

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Abstract

Although direct Cu laser processing of build-up substrates using a carbon dioxide laser is widely used, there are few systematic studies that investigate the detailed characteristics of the machined holes. In this study, all lasers were irradiated under the same conditions, and 3D data were obtained by laser microscopy to determine the hole parameters. A method is then developed to derive the distribution of the machined hole parameters and to predict the performance distribution of the substrate by using high-speed video monitoring images.

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© 2023 The Japan Society for Precision Engineering
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