M
Marc-André Dittrich
Researcher at Leibniz University of Hanover
Publications - 86
Citations - 643
Marc-André Dittrich is an academic researcher from Leibniz University of Hanover. The author has contributed to research in topics: Machining & Machine tool. The author has an hindex of 10, co-authored 82 publications receiving 369 citations. Previous affiliations of Marc-André Dittrich include Massachusetts Institute of Technology.
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Journal ArticleDOI
Exergy analysis of incremental sheet forming
Marc-André Dittrich,Timothy G. Gutowski,Jian Cao,John T. Roth,Z. C. Xia,Vijitha Senaka Kiridena,Feng Ren,Helge Henning +7 more
TL;DR: Using the concept of exergy analysis, two ISF technologies, namely single sided and double sided incremental forming, are investigated and compared to conventional forming and hydroforming and suggest that ISF is environmentally advantageous for prototyping and small production runs.
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Energy efficient machine tools
TL;DR: An overview of current machine- and process-related measures to improve the energy efficiency of metal cutting machine tools and latest developments and already available energy efficiency options in the machine tool industry are discussed.
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Machine Learning Approach for Optimization of Automated Fiber Placement Processes
TL;DR: In this article, a machine learning approach for planning, optimizing and inspection of automated fiber placement (AFP) processes is presented, where data from planning, CNC and online process monitoring is aggregated for the documentation of the part specific manufacturing history and the automated generation of manufacturing knowledge.
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Shifting value stream patterns along the product lifecycle with digital twins
Benjamin Schleich,Marc-André Dittrich,Till Clausmeyer,Roy Gerhardus Johannes Damgrave,John Ahmet Erkoyuncu,Benjamin Haefner,Jos de Lange,Denys Plakhotnik,Wieben Scheidel,Thorsten Wuest +9 more
TL;DR: This article aims to summarize selected recent developments in digital twins and demonstrate use cases from different phases of the product lifecycle and ideas for new value stream patterns using digital twins are envisioned.
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Electrical energy and material efficiency analysis of machining, additive and hybrid manufacturing
TL;DR: In this paper, the authors analyzed and compared the electrical energy and material efficiency of machining, additive and hybrid manufacturing processes based on machine tool data from a sample process and showed that hybrid manufacturing becomes beneficial from an environmental point of view compared to milling, when the material removal ratio exceeds 55%.