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Engineering of additive manufacturing features for data-driven solutions: sources, techniques, pipelines, and applications

From National Research Council Canada

DOIResolve DOI: https://doi.org/10.1007/978-3-031-32154-2
AuthorSearch for: ; Search for: 1; Search for: ; Search for: ; Search for: ORCID identifier: https://orcid.org/0000-0003-4927-0514
Affiliation
  1. National Research Council of Canada. Digital Technologies
FormatText, Book
ISBN978-3-031-32153-5
978-3-031-32154-2
Physical description141 p.
Subjectdata-driven additive manufacturing; feature engineering; data preparation and preprocessing; raw data transformations; representation learning; knowledge engineering; subset selection; mechanistic engineering; 3D printing; machine learning application
Abstract
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 of the status and future of data-driven AM technology.
Publication date
PublisherSpringer
Series
  • SpringerBriefs in Applied Sciences and Technology (1 June 2023).
LanguageEnglish
Peer reviewedYes
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Record identifier36fad027-d2aa-4a27-afc4-0feceb5a3064
Record created2023-06-06
Record modified2023-06-08
Date modified: