Completed
In October 2015 the National Academies of Sciences, Engineering, and Medicine convened a workshop of experts from diverse communities to examine predictive theoretical and computational approaches for various additive manufacturing (AM) technologies. While experimental workshops in AM have been held in the past, this workshop uniquely focused on theoretical and computational approaches and involved areas such as simulation-based engineering and science, integrated computational materials engineering, mechanics, materials science, manufacturing processes, and other specialized areas.
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Workshop
·2016
Additive manufacturing (AM) methods have great potential for promoting transformative research in many fields across the vast spectrum of engineering and materials science. AM is one of the leading forms of advanced manufacturing which enables direct computer-aided design (CAD) to part production wi...
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Description
An ad hoc committee will organize a national workshop on October 7-9, 2015 to discuss the challenges and opportunities in theoretical and computational methods to advance additive manufacturing (AM) in a holistic, multifaceted and interdisciplinary way. Experts from different sectors and industries will share their best practices and ideas to move the field forward.
The workshop will focus on theoretical and computational approaches to additive manufacturing, including areas such as simulation based engineering & science (SBES), integrated computational materials engineering (ICME), mechanics, materials science, manufacturing processes, and other specialized areas. The emphasis of the workshop will be technical, but it will also address policy, and/or other issues related to AM.
The workshop will give researchers in industry, academia, and in the governmental sectors from around the world the opportunity to disseminate the fundamental knowledge that they have obtained related to additive manufacturing processes to contribute to the rapid scientific advancement of those processes. Workshop participants will also suggest short-, intermediate-, and long-term goals for a successful future in predictive methods for AM applications. A rapporteur-authored summary of the workshop will be published.
Collaborators
Sponsors
Department of Defense
Department of Energy
National Science Foundation