Andreas Mayr



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Types of publications

Journal article
Book chapter / Article in edited volumes
Authored book
Translation
Thesis
Edited Volume
Conference contribution
Other publication type
Unpublished / Preprint

Publication year

From
To

Abstract

Journal

Data-driven quality monitoring of bending processes in hairpin stator production using machine learning techniques (2021) Mayr A, Röll P, Winkle D, Enzmann M, Bickel B, Franke J Conference contribution Model improvement through real data connection for Virtual commissioning in ramp-up management of scalable production systems (2021) Kampker A, Wessel S, Lutz N, Heine S, Mayr A, Kuhn A Conference contribution A strategic approach to improve the development of use-oriented knowledge-based engineering configurators (KBEC) (2021) Schäffer E, Shafiee S, Mayr A, Franke J Journal article, Review article Process-Driven Approach within the Engineering Domain by Combining Business Process Model and Notation (BPMN) with Process Engines (2021) Schäffer E, Stiehl V, Schwab P, Mayr A, Lierhammer J, Franke J Journal article, Review article In-situ identification of material batches using machine learning for machining operations (2020) Lutz B, Kißkalt D, Mayr A, Regulin D, Pantano M, Franke J Journal article Prediction of the Joint Cross-Section of Laser-Welded Hairpin Windings Based on 2D Image Data Using Convolutional Neural Networks (2020) Mayr A, Hauck L, Meiners M, Franke J Conference contribution, Conference Contribution Towards an Inline Quality Monitoring for Crimping Processes Utilizing Machine Learning Techniques (2020) Meiners M, Mayr A, Kuhn M, Raab B, Franke J Conference contribution Application of Machine Learning for Product Batch Oriented Control of Production Processes (2020) Meiners M, Mayr A, Thomsen M, Franke J Journal article ForeSight-AI-based Smart Living Platform Approach (2020) Bauer J, Hechtel M, Konrad C, Holzwarth M, Mayr A, Schneider S, Franke J, et al. Journal article Smart use case picking with DUCAR: A hands-on approach for a successful integration of machine learning in production processes (2020) Schäfer F, Mayr A, Schwulera E, Franke J Conference contribution