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Marc-Andre Dittrich
Marc-Andre Dittrich
Institute of Production Engineering and Machine Tools, Leibniz Universität Hannover
Bestätigte E-Mail-Adresse bei ifw.uni-hannover.de - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Energy efficient machine tools
B Denkena, E Abele, C Brecher, MA Dittrich, S Kara, M Mori
CIRP Annals 69 (2), 646-667, 2020
1102020
Exergy analysis of incremental sheet forming
MA Dittrich, TG Gutowski, J Cao, JT Roth, ZC Xia, V Kiridena, F Ren, ...
Production Engineering 6, 169-177, 2012
812012
Machine learning approach for optimization of automated fiber placement processes
J Brüning, B Denkena, MA Dittrich, T Hocke
Procedia CIRP 66, 74-78, 2017
692017
Shifting value stream patterns along the product lifecycle with digital twins
B Schleich, MA Dittrich, T Clausmeyer, R Damgrave, JA Erkoyuncu, ...
Procedia CIRP 86, 3-11, 2019
632019
Electrical energy and material efficiency analysis of machining, additive and hybrid manufacturing
A Wippermann, TG Gutowski, B Denkena, MA Dittrich, Y Wessarges
Journal of Cleaner Production 251, 119731, 2020
582020
Cooperative multi-agent system for production control using reinforcement learning
MA Dittrich, S Fohlmeister
CIRP Annals 69 (1), 389-392, 2020
552020
Self-optimizing tool path generation for 5-axis machining processes
MA Dittrich, F Uhlich, B Denkena
CIRP journal of manufacturing science and technology 24, 49-54, 2019
502019
Inverse determination of constitutive equations and cutting force modelling for complex tools using Oxley's predictive machining theory
B Denkena, T Grove, MA Dittrich, D Niederwestberg, M Lahres
Procedia Cirp 31, 405-410, 2015
382015
Automated production data feedback for adaptive work planning and production control
B Denkena, MA Dittrich, S Wilmsmeier
Procedia Manufacturing 28, 18-23, 2019
332019
Towards dry machining of titanium-based alloys: A new approach using an oxygen-free environment
HJ Maier, S Herbst, B Denkena, MA Dittrich, F Schaper, S Worpenberg, ...
Metals 10 (9), 1161, 2020
302020
Simulation based planning of machining processes with industrial robots
J Brüning, B Denkena, MA Dittrich, HS Park
Procedia Manufacturing 6, 17-24, 2016
272016
Augmenting milling process data for shape error prediction
B Denkena, MA Dittrich, F Uhlich
Procedia CIRP 57, 487-491, 2016
232016
Methodology for integrative production planning in highly dynamic environments
B Denkena, MA Dittrich, S Jacob
Production Engineering 13, 317-324, 2019
222019
Investigations on a standardized process chain and support structure related rework procedures of SLM manufactured components
B Denkena, MA Dittrich, S Henning, P Lindecke
Procedia Manufacturing 18, 50-57, 2018
222018
A deep q-learning-based optimization of the inventory control in a linear process chain
MA Dittrich, S Fohlmeister
Production Engineering 15 (1), 35-43, 2021
212021
Statistical approaches for semi-supervised anomaly detection in machining
B Denkena, MA Dittrich, H Noske, M Witt
Production Engineering 14, 385-393, 2020
212020
Self-optimizing cutting process using learning process models
B Denkena, MA Dittrich, F Uhlich
Procedia Technology 26, 221-226, 2016
212016
Energy efficiency in machining of aircraft components
B Denkena, MA Dittrich, S Jacob
Procedia Cirp 48, 479-482, 2016
202016
Data-based ensemble approach for semi-supervised anomaly detection in machine tool condition monitoring
B Denkena, MA Dittrich, H Noske, D Stoppel, D Lange
CIRP Journal of Manufacturing Science and Technology 35, 795-802, 2021
192021
Automatic regeneration of cemented carbide tools for a resource efficient tool production
B Denkena, MA Dittrich, Y Liu, M Theuer
Procedia Manufacturing 21, 259-265, 2018
182018
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