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.
