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

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 an...

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Bibliographic Details
Main Authors Safdar, Mutahar (Author), Lamouche, Guy (Author), Paul, Padma Polash (Author), Wood, Gentry (Author), Zhao, Yaoyao Fiona (Author)
Format Electronic eBook
LanguageEnglish
Published Cham : Springer, 2023.
SeriesSpringerBriefs in applied sciences and technology,
Subjects
Online AccessFull text
ISBN9783031321542
3031321545
9783031321535
3031321537
ISSN2191-5318
Physical Description1 online resource (xv, 141 pages) : illustrations (some color).

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100 1 |a Safdar, Mutahar,  |e author. 
245 1 0 |a Engineering of additive manufacturing features for data-driven solutions :  |b sources, techniques, pipelines, and applications /  |c Mutahar Safdar, Guy Lamouche, Padma Polash Paul, Gentry Wood, Yaoyao Fiona Zhao. 
264 1 |a Cham :  |b Springer,  |c 2023. 
300 |a 1 online resource (xv, 141 pages) :  |b illustrations (some color). 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a SpringerBriefs in applied sciences and technology,  |x 2191-5318 
505 0 |a Introduction -- Feature Engineering in AM -- Applications in Data-driven AM -- Analyzing AM Feature Spaces -- Challenges and Opportunities in AM Data Preparation -- Summary. 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
520 |a 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. 
504 |a Includes bibliographical references. 
590 |a Knovel  |b Knovel (All titles) 
650 0 |a Additive manufacturing  |x Data processing. 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
655 9 |a electronic books  |2 eczenas 
700 1 |a Lamouche, Guy,  |e author. 
700 1 |a Paul, Padma Polash,  |e author. 
700 1 |a Wood, Gentry,  |e author. 
700 1 |a Zhao, Yaoyao Fiona,  |e author.  |1 https://orcid.org/0000-0003-4927-0514 
776 0 8 |c Original  |z 3031321537  |z 9783031321535  |w (OCoLC)1374814739 
830 0 |a SpringerBriefs in applied sciences and technology,  |x 2191-5318 
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