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Titlebook: Engineering of Additive Manufacturing Features for Data-Driven Solutions; Sources, Techniques, Mutahar Safdar,Guy Lamouche,Yaoyao Fiona Zha

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發(fā)表于 2025-3-21 17:43:35 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Engineering of Additive Manufacturing Features for Data-Driven Solutions
副標題Sources, Techniques,
編輯Mutahar Safdar,Guy Lamouche,Yaoyao Fiona Zhao
視頻videohttp://file.papertrans.cn/312/311030/311030.mp4
概述A comprehensive introduction to data-driven additive manufacturing (AM).Covers all data sources and parts of the AM process.Updates readers with the current challenges and future directions
叢書名稱SpringerBriefs in Applied Sciences and Technology
圖書封面Titlebook: Engineering of Additive Manufacturing Features for Data-Driven Solutions; Sources, Techniques, Mutahar Safdar,Guy Lamouche,Yaoyao Fiona Zha
描述.This book is a comprehensive guide to the latest developments in data-driven additive manufacturing (AM). From data mining and pre-processing to signal processing, computer vision, and more, the book covers all the essential techniques for preparing AM data. Readers willl explore the key physical and synthetic sources of AM data throughout the life cycle of the process and learn about feature engineering techniques, pipelines, and resulting features, as well as their applications at each life cycle phase. With a focus on featurization efforts from reviewed literature, this book offers tabular summaries for major data sources and analyzes feature spaces at the design, process, and structure phases of AM to uncover trends and insights specific to feature engineering techniques. Finally, the book discusses current challenges and future directions, including AI/ML/DL readiness of AM data...Whether you‘re an expert or newcomer to the field, this book provides a broader summary ofthe status and future of?data-driven AM technology..
出版日期Book 2023
關(guān)鍵詞Data-driven Additive Manufacturing; Feature Engineering; Data Preparation and Preprocessing; Raw Data T
版次1
doihttps://doi.org/10.1007/978-3-031-32154-2
isbn_softcover978-3-031-32153-5
isbn_ebook978-3-031-32154-2Series ISSN 2191-530X Series E-ISSN 2191-5318
issn_series 2191-530X
copyrightCrown 2023
The information of publication is updating

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2191-530X with the current challenges and future directions.This book is a comprehensive guide to the latest developments in data-driven additive manufacturing (AM). From data mining and pre-processing to signal processing, computer vision, and more, the book covers all the essential techniques for preparing
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發(fā)表于 2025-3-22 15:46:55 | 只看該作者
https://doi.org/10.1007/978-981-19-3334-9ied and used to group the applications of feature engineering in AM. Their applications are discussed in detail in the subsequent sections of this chapter. A key feature of this chapter is its tabular summaries where detailed feature engineering pipelines are presented and linked with feature source, feature form, and feature applications.
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發(fā)表于 2025-3-22 20:19:19 | 只看該作者
Mutahar Safdar,Guy Lamouche,Yaoyao Fiona ZhaoA comprehensive introduction to data-driven additive manufacturing (AM).Covers all data sources and parts of the AM process.Updates readers with the current challenges and future directions
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https://doi.org/10.1007/978-981-19-3334-9 grouped into design, process, and post-process categories. In each of these categories, major sources of additive manufacturing (AM) data are identified and used to group the applications of feature engineering in AM. Their applications are discussed in detail in the subsequent sections of this cha
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