Production at the leading edge of technology : proceedings of the 12th Congress of the German Academic Association for Production Technology (WGP), Stuttgart, October, 2022 / Mathias Liewald, Alexander Verl, Thomas Bauernhansl, Hans-Christian Möhring, editors.
2023
TS176
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Title
Production at the leading edge of technology : proceedings of the 12th Congress of the German Academic Association for Production Technology (WGP), Stuttgart, October, 2022 / Mathias Liewald, Alexander Verl, Thomas Bauernhansl, Hans-Christian Möhring, editors.
ISBN
9783031183188 (electronic bk.)
3031183185 (electronic bk.)
9783031183171
3031183177
3031183185 (electronic bk.)
9783031183171
3031183177
Published
Cham : Springer, [2023]
Copyright
©2023
Language
English
Description
1 online resource (xvi, 846 pages) : illustrations (chiefly color).
Item Number
10.1007/978-3-031-18318-8 doi
Call Number
TS176
Dewey Decimal Classification
670
Summary
The German Academic Association for Production Technology (WGP) annually invites researchers coming from its institutes and from industry to contribute peer reviewed papers in the field of production technology. This congress proceedings provides recent research results and findings on leading-edge manufacturing processes. Main aim of this scientific congress is to push forward existing borders in production and to provide novel solutions of "Production at the Leading Edge of Manufacturing Technology." Different sessions were held on the topics Recent Developments in Manufacturing Processes Advancements in Production Planning New Approaches in Machine Learning Aspects of Resilience of Production Processes Creating Digital Twins for Production.
Note
Conference proceedings.
Includes author index.
Includes author index.
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Description based on print version record.
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Series
Lecture notes in production engineering.
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Table of Contents
Recent Developments in Manufacturing Processes
Advancements in Production Planning
New Approaches in Machine Learning
Aspects of Resilience of Production Processes
Creating Digital Twins for Production.
Advancements in Production Planning
New Approaches in Machine Learning
Aspects of Resilience of Production Processes
Creating Digital Twins for Production.