Motion and Path Planning for Additive Manufacturing
Idioma: inglés
Editorial: Elsevier, 2023
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N° de ref. del artículo 46130404
- Título
- Motion and Path Planning for Additive Manufacturing
- Autor
- Roschli, Alex C.; Borish, Michael C.; Barnes, Abby K.; Feldhausen, Thomas A.; Wang, Peter
- Editorial
- Elsevier
- Año de publicación
- 2023
- Estado
- As New
- Encuadernación
- Encuadernación de tapa blanda
- Idioma
- inglés
- ISBN 10
- 0443152861
- ISBN 13
- 9780443152863
Motion and Path Planning for Additive Manufacturing takes a deep dive into the concepts and computations behind slicing software - the software that uses 3D models to generate the commands required to control the motion of a 3D printer and ultimately construct objects.
Starting with a brief review of the different types of motion in additive systems, this book walks through the steps of the path planning process and discusses the different types of toolpaths and their corresponding function in additive manufacturing. Planar, non-planar, and off-axis path planning are examined and explained. This book also presents pathing considerations for different types of 3D-printers, including extrusion, non-extrusion, and hybrid systems as well as 3- and 5-axis systems.
Engineers, researchers, and designers in the additive manufacturing field can use this book as a reference for every step of the path planning process, as well as a guide that explains the computations underlying the creation and use of toolpaths.
- Outlines the entire toolpath planning process required to go from a computer-aided design (CAD) model to G-code that a 3D printer can then use to construct a part
- Defines the terms and variables used in slicing and other path-planning software
- Highlights all the available kinematic arrangements for motion systems in additive manufacturing as well as the advantages and risks of each method
- Discusses the nuances of path planning for extrusion, non-extrusion, and hybrid process as well as 3- and 5-axis additive systems
- Provides an up-to-date explanation of advancements in toolpath planning and state-of-the-art slicing processes that use real-time data collection
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Acerca del autor
His current focus is software development for toolpath generation in additive manufacturing. This includes slicing, printing, motor and extrusion control, and closed loop data feedback. Alex manages development of ORNL Slicer 2, a novel toolpath generation software produced at ORNL.
Dr. Michael Borish is a research staff member in the Manufacturing Demonstration Facility (MDF) at Oak Ridge National Laboratory (ORNL), having joined in 2017. At the MDF, he engages in a wide range of disciplines within Computer Science as they relate to industrial additive manufacturing. This research encompasses visualization, augmented reality, path planning, and computer vision, to name a few. He hopes to expand the boundaries of what we define as manufacturing technology. He is also interested in altering established paradigms of operation particularly as it relates to slicing and path planning and has been developing custom slicing software to that end. He has also built an open-source community around slicing software to advance the state of the art in path planning for industrial additive manufacturing.
Abby Barnes is a Research Communications Professional at Oak Ridge National Laboratory's Manufacturing Demonstration Facility. She was previously a researcher in at the University of Tennessee, Knoxville. She has co-authored two research papers and contributed to five others.
Thomas Feldhausen is a research staff member and technical lead for hybrid manufacturing at Oak Ridge National Laboratory's Manufacturing Automation and Controls Group. Hybrid manufacturing, a combination of additive and subtractive (machining) manufacturing, is used in his research at ORNL's Manufacturing Demonstration Facility to provide industrial solutions for component repair, tooling and tooling repair, advanced energy systems, aerospace, and automotive applications. Thomas worked at Honeywell Federal Manufacturing in Kansas City before coming to ORNL, where he specialized in multi-axis additive processes for direct ink-write technology.
Peter Wang is a research staff scientist in the Manufacturing Systems Design Group at Oak Ridge National Laboratory (ORNL). Prior to working at ORNL, he worked in aerospace and underground construction industries for 12 years. His previous work experience has covered mechanical and civil structural design, heavy machine design, project management and construction site automation. He obtained his PhD in 2018 from the University of California, Irvine with a focus in robot kinematics. His current research interests cover robotics, manufacturing systems development, automation, additive manufacturing, and the circular economy.
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