Modeling and identification of an industrial robot for machining applications E Abele, M Weigold, S Rothenbücher CIRP annals 56 (1), 387-390, 2007 | 384 | 2007 |
Cartesian compliance model for industrial robots using virtual joints E Abele, S Rothenbücher, M Weigold Production Engineering 2, 339-343, 2008 | 91 | 2008 |
Machine learning based very short term load forecasting of machine tools B Dietrich, J Walther, M Weigold, E Abele Applied Energy 276, 115440, 2020 | 77 | 2020 |
A systematic review on predicting and forecasting the electrical energy consumption in the manufacturing industry J Walther, M Weigold Energies 14 (4), 968, 2021 | 57 | 2021 |
Kompensation der Werkzeugabdrängung bei der spanenden Bearbeitung mit Industrierobotern M Weigold Shaker, 2008 | 43 | 2008 |
Design and qualification of Pr–Fe–Cu–B alloys for the additive manufacturing of permanent magnets L Schäfer, K Skokov, J Liu, F Maccari, T Braun, S Riegg, I Radulov, ... Advanced Functional Materials 31 (33), 2102148, 2021 | 33 | 2021 |
Machine Learning based quality prediction for milling processes using internal machine tool data A Fertig, M Weigold, Y Chen Advances in Industrial and Manufacturing Engineering 4, 100074, 2022 | 29 | 2022 |
Stress-oriented, data-based payment model for machine tools P Stanula, C Praetzas, O Kohn, J Metternich, M Weigold, A Buchwald Procedia CIRP 93, 1526-1531, 2020 | 23 | 2020 |
Lightweight hybrid CFRP design for machine tools with focus on simple manufacturing F Birk, F Ali, M Weigold, E Abele, K Schützer The International Journal of Advanced Manufacturing Technology 108, 3915-3924, 2020 | 22 | 2020 |
Dimensionless process development for lattice structure design in laser powder bed fusion A Großmann, J Mölleney, T Frölich, H Merschroth, J Felger, M Weigold, ... Materials & Design 194, 108952, 2020 | 21 | 2020 |
CNN-based in situ tool wear detection: A study on model training and data augmentation in turning inserts A García-Pérez, A Ziegenbein, E Schmidt, F Shamsafar, ... Journal of Manufacturing Systems 68, 85-98, 2023 | 20 | 2023 |
Integrating Energy Flexibility in Production Planning and Control-An Energy Flexibility Data Model-Based Approach L Bank, S Wenninger, J Köberlein, M Lindner, C Kaymakci, M Weigold, ... ESSN: 2701-6277, 2021 | 20 | 2021 |
Methodology to determine melt pool anomalies in powder bed fusion of metals using a laser beam by means of process monitoring and sensor data fusion J Harbig, DL Wenzler, S Baehr, MK Kick, H Merschroth, A Wimmer, ... Materials 15 (3), 1265, 2022 | 19 | 2022 |
Influence of LPBF-Surface Characteristics on Fatigue Properties of Scalmalloy® J Musekamp, T Reiber, HC Hoche, M Oechsner, M Weigold, E Abele Metals 11 (12), 1961, 2021 | 18 | 2021 |
Process-influenced fatigue behavior of AISI 316L manufactured by powder-and wire-based Laser Direct Energy Deposition B Blinn, P Lion, O Jordan, S Meiniger, S Mischliwski, C Tepper, C Gläßner, ... Materials Science and Engineering: A 818, 141383, 2021 | 18 | 2021 |
Comparative study of algorithms for optimized control of industrial energy supply systems T Kohne, H Ranzau, N Panten, M Weigold Energy Informatics 3 (Suppl 1), 12, 2020 | 17 | 2020 |
Method for the application of deep reinforcement learning for optimised control of industrial energy supply systems by the example of a central cooling system M Weigold, H Ranzau, S Schaumann, T Kohne, N Panten, E Abele CIRP annals 70 (1), 17-20, 2021 | 16 | 2021 |
Multi-objective hybrid genetic algorithm for energy adaptive production scheduling in job shops B Grosch, T Kohne, M Weigold Procedia CIRP 98, 294-299, 2021 | 16 | 2021 |
Sustainability and Circular Economy in Learning Factories–Case Studies A Weyand, S Thiede, J Mangers, P Plapper, A Ketenci, M Wolf, ... Proceedings of the 12th Conference on Learning Factories (CLF 2022), 2022 | 15 | 2022 |
EuProGigant–A concept towards an industrial system architecture for data-driven production systems S Dumss, M Weber, C Schwaiger, C Sulz, P Rosenberger, F Bleicher, ... Procedia CIRP 104, 324-329, 2021 | 15 | 2021 |