TY - JOUR A1 - Neuber, Till A1 - Schmitt, Anna-Maria A1 - Engelmann, Bastian A1 - Schmitt, Jan T1 - Evaluation of the Influence of Machine Tools on the Accuracy of Indoor Positioning Systems JF - Sensors Y1 - 2022 VL - 22 IS - 24 SP - 10015 EP - 10015 ER - TY - JOUR A1 - Engelmann, Bastian A1 - Schmitt, Simon A1 - Miller, Eddi A1 - Bräutigam, Volker A1 - Schmitt, Jan T1 - Advances in machine learning detecting changeover processes in cyber physical production systems JF - Journal of Manufacturing and Materials Processing N2 - The performance indicator, Overall Equipment Effectiveness (OEE), is one of the most important ones for production control, as it merges information of equipment usage, process yield, and product quality. The determination of the OEE is oftentimes not transparent in companies, due to the heterogeneous data sources and manual interference. Furthermore, there is a difference in present guidelines to calculate the OEE. Due to a big amount of sensor data in Cyber Physical Production Systems, Machine Learning methods can be used in order to detect several elements of the OEE by a trained model. Changeover time is one crucial aspect influencing the OEE, as it adds no value to the product. Furthermore, changeover processes are fulfilled manually and vary from worker to worker. They always have their own procedure to conduct a changeover of a machine for a new product or production lot. Hence, the changeover time as well as the process itself vary. Thus, a new Machine Learning based concept for identification and characterization of machine set-up actions is presented. Here, the issue to be dealt with is the necessity of human and machine interaction to fulfill the entire machine set-up process. Because of this, the paper shows the use case in a real production scenario of a small to medium size company (SME), the derived data set, promising Machine Learning algorithms, as well as the results of the implemented Machine Learning model to classify machine set-up actions. Y1 - 2020 UR - https://www.proquest.com/docview/2461685989?pq-origsite=gscholar&fromopenview=true VL - 4 IS - 4 SP - 108 EP - 108 ER - TY - JOUR A1 - Engelmann, Bastian A1 - Schmitt, Anna-Maria A1 - Theilacker, Lukas A1 - Schmitt, Jan T1 - Implications from Legacy Device Environments on the Conceptional Design of Machine Learning Models in Manufacturing JF - Journal of Manufacturing and Materials Processing Y1 - 2024 UR - https://doi.org/10.3390/jmmp8010015 VL - 2024 ER - TY - JOUR A1 - Schmitt, Anna-Maria A1 - Miller, Eddi A1 - Engelmann, Bastian A1 - Batres, Rafael A1 - Schmitt, Jan T1 - G-code evaluation in CNC milling to predict energy consumption through Machine Learning JF - Advances in Industrial and Manufacturing Engineering N2 - Computerized Numeric Control (CNC) plays an essential role in highly autonomous manufacturing systems for interlinked process chains for machine tools. NC-programs are mostly written in standardized G-code. Evaluating CNC-controlled manufacturing processes before their real application is advantageous due to resource efficiency. One dimension is the estimation of the energy demand of a part manufactured by an NC-program, e.g. to discover optimization potentials. In this context, this paper presents a Machine Learning (ML) approach to assess G-code for CNC-milling processes from the perspective of the energy demand of basic G-commands. We propose Latin Hypercube Sampling as an efficient method of Design of Experiments to train the ML model with minimum experimental effort to avoid costly setup and implementation time of the model training and deployment. KW - Machine Learning KW - CNC machine tools KW - G-code KW - Energy consumption Y1 - 2024 UR - https://doi.org/10.1016/j.aime.2024.100140 VL - 2024 IS - 8 ER - TY - JOUR A1 - Stühm, Kai A1 - Tornow, Alexander A1 - Schmitt, Jan A1 - Grunau, Leonard A1 - Dietrich, Franz A1 - Dröder, Klaus T1 - A novel gripper for battery electrodes based on the Bernoulli-principle with integrated exhaust air compensation JF - Procedia CIRP Y1 - 2014 VL - 23 SP - 161 EP - 164 ER - TY - CHAP A1 - Schmitt, Jan A1 - Inkermann, David A1 - Stechert, Carsten A1 - Raatz, Annika A1 - Vietor, Thomas T1 - Requirement oriented reconfiguration of parallel robotic systems T2 - Robotic Systems-Applications, Control and Programming Y1 - 2012 SP - 387 EP - 410 ER - TY - JOUR A1 - Jan Schmitt, Kai Stühm, Annika Raatz, Klaus Dröder T1 - Simulating production effects on lithium-ion batteries JF - AABC Y1 - 2013 ER - TY - CHAP A1 - Cerdas, Felipe A1 - Gerbers, Roman A1 - Andrew, Stefan A1 - Schmitt, Jan A1 - Dietrich, Franz A1 - Thiede, Sebastian A1 - Dröder, Klaus A1 - Herrmann, Christoph T1 - Disassembly planning and assessment of automation potentials for lithium-ion batteries T2 - Recycling of Lithium-Ion Batteries: The LithoRec Way Y1 - 2018 SP - 83 EP - 97 ER - TY - JOUR A1 - Herrmann, Christoph A1 - Raatz, Annika A1 - Andrew, Stefan A1 - Schmitt, Jan T1 - Scenario-based development of disassembly systems for automotive lithium ion battery systems JF - Advanced Materials Research Y1 - 2014 VL - 907 SP - 391 EP - 401 ER - TY - JOUR A1 - Schmitt, Jan A1 - Raatz, Annika A1 - Dietrich, Franz A1 - Dröder, Klaus A1 - Hesselbach, Jürgen T1 - Process and performance optimization by selective assembly of battery electrodes JF - CIRP Annals Y1 - 2014 VL - 63 IS - 1 SP - 9 EP - 12 ER - TY - JOUR A1 - Schilling, Antje A1 - Schmitt, Jan A1 - Dietrich, Franz A1 - Dröder, Klaus T1 - Analyzing Bending Stresses on Lithium-Ion Battery Cathodes induced by the Assembly Process JF - Energy Technology Y1 - 2016 VL - 4 IS - 12 SP - 1502 EP - 1508 ER - TY - JOUR A1 - Schmitt, Jan A1 - Raatz, Annika T1 - Failure Mode Based Design and Optimization of the Electrode Packaging Process for Large Scale Battery Cells JF - Advanced Materials Research Y1 - 2014 VL - 907 SP - 309 EP - 319 ER - TY - THES A1 - Schmitt, Jan T1 - Untersuchungen zum Herstellungsprozess des Elektrode-Separator-Verbunds für Lithium-Ionen Batteriezellen Y1 - 2015 ER - TY - JOUR A1 - Schmitt, Jan A1 - Seitz, Philipp A1 - Scherdel, Christian A1 - Reichenauer, Gudrun T1 - Machine Learning in the development of Si-based anodes using Small-Angle X-ray Scattering for structural property analysis JF - Computational Materials Science N2 - Material development processes are highly iterative and driven by the experience and intuition of the researcher. This can lead to time consuming procedures. Data-driven approaches such as Machine Learning can support decision processes with trained and validated models to predict certain output parameter. In a multifaceted process chain of material synthesis of electrochemical materials and their characterization, Machine Learning has a huge potential to shorten development processes. Based on this, the contribution presents a novel approach to utilize data derived from Small-Angle X-ray Scattering (SAXS) of SiO_2 matrix materials for battery anodes with Neural Networks. Here, we use SAXS as an intermediate, high-throughput method to characterize sol–gel based porous materials. A multi-step-method is presented where a Feed Forward Net is connected to a pretrained autoencoder to reliably map parameters of the material synthesis to the SAXS curve of the resulting material. In addition, a direct comparison shows that the prediction error of Neural Networks can be greatly reduced by training each output variable with a separate independent Neural Network. KW - machine learning KW - neural network KW - autoencoder Y1 - 2023 UR - https://doi.org/10.1016/j.commatsci.2022.111984 SN - 1879-0801 N1 - Link zum Datensatz: https://gitlab.vlab.fm.fhws.de/philipp.seitz/machinelearningandsaxs VL - 218 ER - TY - CHAP A1 - Schmitt, Jan A1 - Bruhn, Matthias A1 - Raatz, Annika T1 - Comparative analysis of pneumatic grippers for handling operations of crystalline solar cells T2 - Proceedings of the IASTED Asian Conference on Power and Energy Systems, AsiaPES Y1 - 2012 SP - 386 EP - 392 ER - TY - CHAP A1 - Herrmann, Christoph A1 - Raatz, Annika A1 - Mennenga, Mark A1 - Schmitt, Jan A1 - Andrew, Stefan T1 - Assessment of automation potentials for the disassembly of automotive lithium ion battery systems T2 - Leveraging Technology for a Sustainable World: Proceedings of the 19th CIRP Conference on Life Cycle Engineering, University of California at Berkeley, Berkeley, USA, May 23-25, 2012 Y1 - 2012 SP - 149 EP - 154 ER - TY - CHAP A1 - Schmitt, Jan A1 - Treuer, F A1 - Dietrich, F A1 - Dröder, K A1 - Heins, T-P A1 - Schröder, U A1 - Westerhoff, U A1 - Kurrat, M A1 - Raatz, A T1 - Coupled mechanical and electrochemical characterization method for battery materials T2 - 2014 IEEE Conference on Energy Conversion (CENCON) Y1 - 2014 SP - 395 EP - 400 ER - TY - CHAP A1 - Schreiber, Frank A1 - Sklyarenko, Yevgen A1 - Schlüter, Kathrin A1 - Schmitt, Jan A1 - Rost, Sven A1 - Raatz, Annika A1 - Schumacher, Walter T1 - Tracking control with hysteresis compensation for manipulator segments driven by pneumatic artificial muscles T2 - 2011 IEEE international conference on robotics and biomimetics Y1 - 2011 SP - 2750 EP - 2755 ER - TY - CHAP A1 - Schmitt, Jan A1 - Haupt, Hannes A1 - Kurrat, Michael A1 - Raatz, Annika T1 - Disassembly automation for lithium-ion battery systems using a flexible gripper T2 - 2011 15th International Conference on Advanced Robotics (ICAR) Y1 - 2011 SP - 291 EP - 297 ER - TY - CHAP A1 - Schmitt, Jan A1 - Last, Philipp A1 - Lochte, Christian A1 - Raatz, Annika A1 - Hesselbach, Jürgen T1 - TRoBS - a biological inspired robot T2 - 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO) Y1 - 2009 SP - 51 EP - 56 ER -