Engineering of Additive Manufacturing Features for Data-Driven Solutions [electronic resource] : Sources, Techniques, Pipelines, and Applications / by Mutahar Safdar, Guy Lamouche, Padma Polash Paul, Gentry Wood, Yaoyao Fiona Zhao.

Por: Safdar, Mutahar [author.]Colaborador(es): Lamouche, Guy [author.] | Paul, Padma Polash [author.] | Wood, Gentry [author.] | Zhao, Yaoyao Fiona [author.] | SpringerLink (Online service)Tipo de material: TextoTextoSeries SpringerBriefs in Applied Sciences and TechnologyEditor: Cham : Springer Nature Switzerland : Imprint: Springer, 2023Edición: 1st ed. 2023Descripción: XV, 141 p. 43 illus., 37 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783031321542Tema(s): Industrial engineering | Production engineering | Engineering -- Data processing | Artificial intelligence | Machine learning | Education | Industrial and Production Engineering | Data Engineering | Artificial Intelligence | Machine Learning | EducationFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 670 Clasificación LoC:T55.4-60.8Recursos en línea: Libro electrónicoTexto
Contenidos:
Introduction -- Feature Engineering in AM -- Applications in Data-driven AM -- Analyzing AM Feature Spaces -- Challenges and Opportunities in AM Data Preparation -- Summary.
En: Springer Nature eBookResumen: 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.
Star ratings
    Valoración media: 0.0 (0 votos)
Existencias
Tipo de ítem Biblioteca actual Colección Signatura Copia número Estado Fecha de vencimiento Código de barras
Libro Electrónico Biblioteca Electrónica
Colección de Libros Electrónicos 1 No para préstamo

Acceso multiusuario

Introduction -- Feature Engineering in AM -- Applications in Data-driven AM -- Analyzing AM Feature Spaces -- Challenges and Opportunities in AM Data Preparation -- Summary.

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.

UABC ; Perpetuidad

Con tecnología Koha