Stability of Pharmaceutical Co-Crystals at Humid Conditions Can Be Predicted von Veith, Heiner, Zaeh, Maximilian, Luebbert, Christian, Rodríguez-Hornedo, Naír, Sadowski, Gabriele

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Predicting the amorphous-phase composition during lyophilization von Zäh, Maximilian, Brandenbusch, Christoph, Winter, Gerhard, Sadowski, Gabriele

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DSC reveals the excipient impact on aggregation propensity of pharmaceutical peptides during freezing von Zäh, Maximilian, Brandenbusch, Christoph, Artusio, Fiora, Sadowski, Gabriele, Pisano, Roberto

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Characterization of Polymeric Syringes Used for Intravitreal Injection von Peláez, Sarah S., Mahler, Hanns-Christian, Koulov, Atanas, Joerg, Susanne, Matter, Anja, Vogt, Martin, Chalus, Pascal, Zaeh, Maximilian, Sediq, Ahmad S., Jere, Dhananjay, Mathaes, Roman

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Condition monitoring of ball screw feed drives using convolutional neural networks von Benker, Maximilian, Zaeh, Michael F.

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Corrigendum to ‘Condition monitoring of ball screw feed drives using convolutional neural networks’ [CIRP Annals - Manufacturing Technology 71 (2022) 313-316] von Benker, Maximilian, Zaeh, Michael F.

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Multi-Fidelity Information Fusion to Model the Position-Dependent Modal Properties of Milling Robots von Busch, Maximilian, Zaeh, Michael F.

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Utilizing uncertainty information in remaining useful life estimation via Bayesian neural networks and Hamiltonian Monte Carlo von Benker, Maximilian, Furtner, Lukas, Semm, Thomas, Zaeh, Michael F.

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Methodology for model-based uncertainty quantification of the vibrational properties of machining robots von Busch, Maximilian, Schnoes, Florian, Elsharkawy, Amr, Zaeh, Michael F.

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A Gaussian Process Based Method for Data- Efficient Remaining Useful Life Estimation von Benker, Maximilian, Bliznyuk, Artem, Zaeh, Michael F.

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A Novel Approach to the Holistic 3D Characterization of Weld Seams—Paving the Way for Deep Learning-Based Process Monitoring von Schmoeller, Maximilian, Stadter, Christian, Kick, Michael Karl, Geiger, Christian, Zaeh, Michael Friedrich

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Automation of Experimental Modal Analysis Using Bayesian Optimization von Ellinger, Johannes, Beck, Leopold, Benker, Maximilian, Hartl, Roman, Zaeh, Michael F.

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Predicting the Ultimate Tensile Strength of Friction Stir Welds Using Gaussian Process Regression von Hartl, Roman, Vieltorf, Fabian, Benker, Maximilian, Zaeh, Michael F.

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Real-time prediction of quality characteristics in laser beam welding using optical coherence tomography and machine learning von Stadter, Christian, Schmoeller, Maximilian, von Rhein, Lara, Zaeh, Michael F.

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Segmentation-based closed-loop layer height control for enhancing stability and dimensional accuracy in wire-based laser metal deposition von Bernauer, Christian, Leitner, Philipp, Zapata, Avelino, Garkusha, Pawel, Grabmann, Sophie, Schmoeller, Maximilian, Zaeh, Michael F.

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Inline Weld Depth Evaluation and Control Based on OCT Keyhole Depth Measurement and Fuzzy Control von Schmoeller, Maximilian, Weiss, Tony, Goetz, Korbinian, Stadter, Christian, Bernauer, Christian, Zaeh, Michael F.

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Inline weld depth measurement for high brilliance laser beam sources using optical coherence tomography von Schmoeller, Maximilian, Stadter, Christian, Liebl, Stefan, Zaeh, Michael F.

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Process control and quality assurance in remote laser beam welding by optical coherence tomography von Stadter, Christian, Schmoeller, Maximilian, Zeitler, Martin, Tueretkan, Volkan, Munzert, Ulrich, Zaeh, Michael F.

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Numerical weld pool simulation for the accuracy improvement of inline weld depth measurement based on optical coherence tomography von Schmoeller, Maximilian, Neureiter, Maximilian, Stadter, Christian, Zaeh, Michael F.

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Probabilistic information fusion to model the pose-dependent dynamics of milling robots von Busch, Maximilian, Schnoes, Florian, Semm, Thomas, Zaeh, Michael F., Obst, Birgit, Hartmann, Dirk

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