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 will explore the key physical and...

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Bibliographic Details
Published inSpringerBriefs in Applied Sciences and Technology
Main Authors Safdar, Mutahar, Lamouche, Guy, Paul, Padma Polash, Wood, Gentry, Zhao, Yaoyao Fiona
Format eBook Book
LanguageEnglish
Published Cham Springer Nature 2023
Springer
Springer Nature Switzerland
Edition1
SeriesSpringerBriefs in Applied Sciences and Technology
Subjects
3D printing
Additive manufacturing
Artificial Intelligence
Data Engineering
data preparation and preprocessing
data-driven additive manufacturing
Education, general
Engineering
feature engineering
Industrial and Production Engineering
knowledge engineering
Machine Learning
machine learning application
Manufacturing Engineering
Materials & Manufacturing Processes
mechanistic engineering
raw data transformations
representation learning
subset selection
Online AccessGet full text
ISBN3031321537
9783031321535
3031321545
9783031321542
ISSN2191-5318
2191-530X
2191-5318
DOI10.1007/978-3-031-32154-2

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Table of Contents:
  • Title Page Abbreviations Table of Contents 1. Introduction 2. Feature Engineering in Additive Manufacturing 3. Applications in Data-Driven Additive Manufacturing 4. Analyzing Additive Manufacturing Feature Spaces 5. Challenges and Opportunities in Additive Manufacturing Data Preparation 6. Summary