@article{HoefflinSauerSchiffleretal., author = {H{\"o}fflin, Dennis and Sauer, Christian and Schiffler, Andreas and Manara, Jochen and Hartmann, J{\"u}rgen}, title = {Pixelwise high-temperature calibration for in-situ temperature measuring in powder bed fusion of metal with laser beam}, series = {Heliyon}, volume = {10}, journal = {Heliyon}, number = {7}, publisher = {Elsevier BV}, issn = {2405-8440}, doi = {10.1016/j.heliyon.2024.e28989}, abstract = {High-temperature calibration methods in additive manufacturing involve the use of advanced techniques to accurately measure and control the temperature of the build material during the additive manufacturing process. Infrared cameras, blackbody radiation sources and non-linear optimization algorithms are used to correlate the temperature of the material with its emitted thermal radiation. This is essential for ensuring the quality and repeatability of the final product. This paper presents the calibration procedure of an imaging system for in-situ measurement of absolute temperatures and temperature gradients during powder bed fusion of metal with laser beam (PBF-LB/M) in the temperature range of 500 K-1500 K. It describes the design of the optical setup to meet specific requirements in this application area as well as the procedure for accounting the various factors influencing the temperature measurement. These include camera-specific effects such as varying spectral sensitivities of the individual pixels of the sensor as well as influences of the exposure time and the exposed sensor area. Furthermore, influences caused by the complex optical path, such as inhomogeneous transmission properties of the galvanometer scanner as well as angle-dependent transmission properties of the f-theta lens were considered. A two-step fitting algorithm based on Planck's law of radiation was applied to best represent the correlation. With the presented procedure the calibrated thermography system provides the ability to measure absolute temperatures under real process conditions with high accuracy.}, language = {en} } @article{MartinezSchmittSchiffleretal., author = {Martinez, Mario and Schmitt, Anna-Maria and Schiffler, Andreas and Engelmann, Bastian}, title = {Production Data Set for five-Axis CNC Milling with multiple Changeovers}, series = {Scientific Data}, volume = {12}, journal = {Scientific Data}, number = {1}, publisher = {Springer Science and Business Media LLC}, issn = {2052-4463}, doi = {https://doi.org/10.1038/s41597-025-05294-0}, abstract = {Abstract This data descriptor contains information about an extensive production data set for a five-axis CNC milling process. Three geometrically different products were manufactured and relevant features from the numerical control of the machine were recorded. The recorded manufacturing process contains the preparation of the machine for the next product (changeover) as well as the machining process (production). The experimental manufacturing was organized with the aid of a changeover matrix to ensure that all possible changeover combinations for the three products were considered. The production was repeated five times, resulting in 30 manufacturing sessions and five complete changeover matrices. The data set was recorded in a laboratory environment. A rich feature set including i.e. the NC-code of the products, tool information, and a Jupyter notebook is provided with the data set.}, language = {en} } @misc{HoefflinSchifflerHartmannetal., author = {H{\"o}fflin, Dennis and Schiffler, Andreas and Hartmann, J{\"u}rgen and Sauer, Christian}, title = {Dual Scan head approach for in-situ defect detection in laser powder bed fusion of metals - Dataset}, doi = {10.5281/zenodo.15727369}, abstract = {This dataset contains thermographic data from a study on in-situ defect detection in the Laser Powder Bed Fusion of Metals (PBF-LB/M) process. The data was collected using a novel experimental setup named Synchronized Path Infrared Thermography (SPIT), which employs a dual scan head configuration. One scan head directs the processing laser, while the second scan head positions the measurement field of an infrared (IR) camera. This setup allows for the precise analysis of the cooling behavior of the material decoupled from the immediate laser-material interaction zone. The experiments were conducted on pre-fabricated stainless steel (EOS StainlessSteel PH1, DIN 14540) samples with embedded, cylindrical subsurface defects of varying diameters. A single layer of metal powder was applied to these samples and then fused by the laser. The dataset includes a series of measurements where process parameters, specifically the volumetric energy density and the laser scanning speed, were systematically varied to assess their influence on defect detection reliability. The provided data consists of raw thermographic recordings, which capture the surface temperature distribution in the heat-affected zone behind the melt pool. These recordings can be used to identify localized areas of elevated temperature caused by the insulating effect of the subsurface defects, which impede heat transfer into the substrate. This dataset is valuable for researchers working on process monitoring, defect detection algorithms, and the validation of thermal simulations in additive manufacturing.}, language = {en} } @misc{SauerSchifflerHoefflinetal., author = {Sauer, Christian and Schiffler, Andreas and H{\"o}fflin, Dennis and Hartmann, J{\"u}rgen}, title = {Temporally Gated Active Thermography for Defect Detection in Laser-Based Powder Bed Fusion of Metals - Dataset}, doi = {10.5281/zenodo.17747278}, abstract = {This HDF5-dataset contains in-situ high-speed infrared thermography data acquired during the Laser-Based Powder Bed Fusion (PBF-LB/M) process. The data was collected using a Synchronized Path Infrared Thermography (SPIT) setup, which employs a dual-scanhead configuration to guide both the processing laser and the thermal camera's field of view. The primary feature of this dataset is the application of a temporally gated acquisition strategy. The infrared camera's integration time (800 µs) was synchronized with a modulated processing laser (500 Hz) to capture thermal data exclusively during the laser-off phases. This method effectively isolates the material's thermal emission from high-intensity laser reflections.}, language = {en} } @article{HoefflinHartmannRosiliusetal., author = {H{\"o}fflin, Dennis and Hartmann, J{\"u}rgen and Rosilius, Maximilian and Seitz, Philipp and Schiffler, Andreas}, title = {Opto-Thermal Investigation of Additively Manufactured Steel Samples as a Function of the Hatch Distance}, series = {Sensors}, volume = {22}, journal = {Sensors}, number = {1}, publisher = {MDPI}, issn = {1424-8220}, doi = {10.3390/s22010046}, pages = {46}, abstract = {Nowadays, additive manufacturing processes are becoming more and more appealing due to their production-oriented design guidelines, especially with regard to topology optimisation and minimal downstream production depth in contrast to conventional technologies. However, a scientific path in the areas of quality assurance, material and microstructural properties, intrinsic thermal permeability and dependent stress parameters inhibits enthusiasm for the potential degrees of freedom of the direct metal laser melting process (DMLS). Especially in quality assurance, post-processing destructive measuring methods are still predominantly necessary in order to evaluate the components adequately. The overall objective of these investigations is to gain process knowledge make reliable in situ statements about component quality and material properties based on the process parameters used and emission values measured. The knowledge will then be used to develop non-destructive tools for the quality management of additively manufactured components. To assess the effectiveness of the research design in relation to the objectives for further investigations, this pre-study evaluates the dependencies between the process parameters, process emission during manufacturing and resulting thermal diffusivity and the relative density of samples fabricated by DMLS. Therefore, the approach deals with additively built metal samples made on an EOS M290 apparatus with varying hatch distances while simultaneously detecting the process emission. Afterwards, the relative density of the samples is determined optically, and thermal diffusivity is measured using the laser flash method. As a result of this pre-study, all interactions of the within factors are presented. The process variable hatch distance indicates a strong influence on the resulting material properties, as an increase in the hatch distance from 0.11 mm to 1 mm leads to a drop in relative density of 57.4\%. The associated thermal diffusivity also reveals a sharp decrease from 5.3 mm2/s to 1.3 mm2/s with growing hatch distances. The variability of the material properties can also be observed in the measured process emissions. However, as various factors overlap in the thermal radiation signal, no clear assignment is possible within the scope of this work.}, language = {en} } @article{SchifflerWehnertOchs, author = {Schiffler, Andreas and Wehnert, Kira-Kristin and Ochs, Dennis}, title = {Einsatz einer maschinell gelernten Bildsegmentierung zur Pulverbett{\"u}berwachung im Metalldruck}, series = {FHWS Science Journal}, volume = {5}, journal = {FHWS Science Journal}, number = {2}, issn = {2196-6095}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:863-opus-20021}, pages = {147 -- 152}, abstract = {Der Schwerpunkt der folgenden Ausf{\"u}hrungen ist auf eine schichtweise Erkennung von Abweichungen durch die automatisierte Analyse von Bilddaten aus pulverbettbasierten Metalldruckprozessen gelegt. Bei diesen Prozessen wird eine d{\"u}nne Schicht im Bereich von 20 bis 100 μm aus pulverf{\"o}rmigem Metallpulver aufgetragen. Ein zweidimensionaler Querschnitt des gew{\"u}nschten Bauteils wird dann entweder mit einer selektiven W{\"a}rmequelle aufgeschmolzen oder mit einem Bindemittel zusammengebunden. Anschließend wird das Substrat um die H{\"o}he einer Pulverschicht abgesenkt und der Vorgang wiederholt, bis der Aufbau abgeschlossen ist. Nach dem Abschluss des Aufschmelzens einer Schicht wird ein Bild mittels einer Kamera im sichtbaren Wellenl{\"a}ngenbereich erstellt. Abbildung 1 zeigt zwei Beispiele solcher Bilder. Diese bilden die Eingangsgr{\"o}ße f{\"u}r die Erkennung von Abweichungen. Durch die gew{\"a}hlte Schichtdicke kann die Herstellung eines Bauteils mehrere tausend Bilder erzeugen. Die automatisierte und zeitnahe Auswertung ist daher Inhalt aktueller Forschungs- und Entwicklungsaktivit{\"a}ten [1]. Nicht zuletzt da die notwendige Sensorik - eine Kamera - wirtschaftlich und robust einsetzbar ist.}, language = {de} } @article{MillerBarthelmeSchiffleretal., author = {Miller, Eddi and Barthelme, Christine and Schiffler, Andreas and Engelmann, Bastian and Schmitt, Jan}, title = {Internationalisierung in Pandemiezeiten, technische M{\"o}glichkeiten, Lehr- und Forschungskonzepte mal anders gedacht}, series = {FHWS Science Journal}, volume = {5}, journal = {FHWS Science Journal}, number = {2}, issn = {2196-6095}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:863-opus-20035}, pages = {143 -- 146}, abstract = {Eines der zentralen strategischen Ziele unserer Hochschule ist die Internationalisierung, sowie der »internationalisation@home«. Als die weltweite Corona-Pandemie die Pr{\"a}senzlehre und -forschung ebenso wie den internationalen Austausch von Studierenden und Forschenden zu Beginn 2020 quasi zum Erliegen brachte wurden die Rufe nach digitalen Angeboten im internationalen Bereich schnell laut. Vor diesem Hintergrund reagierte der »Deutsche Akademische Auslandsdienst (DAAD)« mit der kurzfristig ins Leben gerufenen F{\"o}rderlinie »International Virtual Academic Collaboration« (IVAC), um internationale Hochschulkooperationen und weltweite Mobilit{\"a}t unter digitalen Vorzeichen strategisch zu gestalten und auszubauen [1].}, language = {de} } @article{WehnertOchsSchmittetal., author = {Wehnert, Kira-Kristin and Ochs, Dennis and Schmitt, Jan and Hartmann, J{\"u}rgen and Schiffler, Andreas}, title = {Reducing Lifecycle Costs due to Profile Scanning of the Powder Bed in Metal Printing}, series = {Procedia CIRP 98}, volume = {98}, journal = {Procedia CIRP 98}, publisher = {Elsevir}, pages = {684 -- 689}, abstract = {First time right is one major goal in powder based 3D metal printing. Reaching this goal is driven by reducing life cycle costs for quality measures, to minimize scrap rate and to increase productivity under optimal resource efficiency. Therefore, monitoring the state of the powder bed for each printed layer is state of the art in selective laser melting. In the most modern approaches the quality monitoring is done by computer vision systems working with an interference on trained neural networks with images taken after exposure and after recoating. There are two drawbacks of this monitoring method: First, the sensor signals - the image of the powder bed - give no direct height information. Second, the application of this method needs to be trained and labeled with reference images for several cases. The novel approach presented in this paper uses a laser line scanner attached to the recoating machine. With this new concept, a direct threshold measure can be applied during the recoating process to detect deviations in height level without prior knowledge. The evaluation can be done online during recoating and feedback to the controller to monitor each individual layer. Hence, in case of deviations the location in the printing plane is an inherent measurement and will be used to decide which severity of error is reported. The signal is used to control the process, either by starting the recoating process again or stopping the printing process. With this approach, the sources of error for each layer can be evaluated with deep information to evaluate the cause of the error. This allows a reduction of failure in the future, which saves material costs, reduces running time of the machine life cycle phase in serial production and results in less rework for manufactured parts. Also a shorter throughput time per print job results, which means that the employee can spent more time to other print jobs and making efficient use of the employee's work force. In summary, this novel approach will not only reduce material costs but also operating costs and thus optimize the entire life cycle cost structure. The paper presents a first feasibility and application of the described approach for test workpieces in comparison to conventional monitoring systems on an EOS M290 machine.}, language = {en} } @article{SchmittSauerHoefflinetal., author = {Schmitt, Anna-Maria and Sauer, Christian and H{\"o}fflin, Dennis and Schiffler, Andreas}, title = {Powder Bed Monitoring Using Semantic Image Segmentation to Detect Failures during 3D Metal Printing}, series = {Sensors}, volume = {23}, journal = {Sensors}, number = {9}, publisher = {MDPI}, doi = {10.3390/s23094183}, pages = {4183 -- 4183}, abstract = {Monitoring the metal Additive Manufacturing (AM) process is an important task within the scope of quality assurance. This article presents a method to gain insights into process quality by comparing the actual and target layers. Images of the powder bed were captured and segmented using an Xception-style neural network to predict the powder and part areas. The segmentation result of every layer is compared to the reference layer regarding the area, centroids, and normalized area difference of each part. To evaluate the method, a print job with three parts was chosen where one of them broke off and another one had thermal deformations. The calculated metrics are useful for detecting if a part is damaged or for identifying thermal distortions. The method introduced by this work can be used to monitor the metal AM process for quality assurance. Due to the limited camera resolutions and inconsistent lighting conditions, the approach has some limitations, which are discussed at the end.}, language = {en} } @misc{SeyboldWegnerGluecketal., author = {Seybold, Alexander and Wegner, Christoph and Gl{\"u}ck, Stefan and Schiffler, Andreas and Voll, Martin}, title = {Measuring system for monitoring a spindle (Patent, US-20210187684-A1)}, language = {en} } @inproceedings{LutzKisskaltRegulinetal., author = {Lutz, Benjamin and Kisskalt, Dominik and Regulin, Daniel and Reisch, Raven and Schiffler, Andreas and Franke, J{\"o}rg}, title = {Evaluation of deep learning for semantic image segmentation in tool condition monitoring}, series = {2019 18th IEEE international conference on machine learning and applications (ICMLA)}, booktitle = {2019 18th IEEE international conference on machine learning and applications (ICMLA)}, pages = {2008 -- 2013}, language = {en} } @article{SchifflerRunde, author = {Schiffler, Andreas and Runde, Stefan}, title = {CNC-Shopfloor-Management Ein neuer Weg zum optimalen NC-Programm}, series = {Digital Manufactoring}, journal = {Digital Manufactoring}, number = {03/2019}, pages = {10 -- 14}, language = {en} }