Fraunhofer Austria
Fraunhofer Austria

Wissenschaftliche Publikationen

Alle ausklappen Alle einklappen

  1. Kurt Battisti, Markus Dörn, Eva Eggeling, Christoph Eichler, Jan Morten Loës, Jacqueline Scherret, Zolbayasakh Tsoggerel, Torsten Ullrich:
    »An Automatic Process for the Application of Building Permits«,
    Buildings, 2023, Band 13, Seite 78,  https://doi.org/10.3390/buildings13010078
  2. Max von Buelow, Arjan Kuijper, Dieter W. Fellner:
    »A GPU Ray Tracing Implementation for Triangular Grid Primitives«,
    in:  ICAT-EGVE 2023, International Conference on Artificial Reality and Telexistence and Eurographics Symposium on Virtual Environments, 2023, https://doi.org/10.2312/egve.20231341
  3. Alexandra Birkmaier, Adhurim Imeri, Martin Riester, Gerald Reiner:
    »Preventing waste in food supply networks-a platform architecture for AI-driven forecasting based on heterogeneous big data«,
    Procedia CIRP, 2023, Band 120, Seite 708-713, https://doi.org/10.1016/j.procir.2023.09.063
  4. Leonhard Czarnetzki, Catherine Laflamme, Christoph Halbwidl, Lisa Charlotte Günther, Thomas Sobottka, Daniel Bachlechner:
    »Optimisation of Matrix Production System Reconfiguration with Reinforcement Learning«,
    KI2023: 46th German Conference on AI, Berlin, Germany, Proceedings, Seite 15-22
  5. Leonhard Czarnetzki, David Karnok, Johannes Breitschopf, Matthias Karner, Milot Gashi, Thomas Mambrini, Catherine Laflamme, Viola Gallina, Wilfried Sihn:
    »Improving the Planning Quality in Practice with Artificial Intelligence«,
    TC10 Conference 2023, DOI: 10.21014/tc10-2023.004
  6. Giacomo Da Col, Eva Eggeling, Marco Hudelist, Christoph Schinko, Christof Surtmann, Erich Teppan:
    »Sensorbasierte Feuchtigkeitsprognose für Flachdächer«,
    Jahrbuch Instandhaltungstage, 2023, Seite 136-138, ISBN 978-3-7011-0514-4
  7. Giacomo Da Col, Erich Teppan:
    »Pursuing the Optimal CP Model: A Batch Scheduling Case Study«,
    Intelligent Systems and Applications, 2023, Band 822, Seite 508-520, https://doi.org/10.1007/978-3-031-47721-8_34
  8. Fabio Del Ben, Giacomo Da Col, Doriana Cobârzan, Matteo Turetta, Daniela Rubin, Patrizio Buttazzi, Antonio Antico:
    »A fully interpretable machine learning model for increasing the effectiveness of urine screening«,
    American Journal of Clinical Pathology, 2023, Band 160, Seite 620-632, https://doi.org/10.1093/ajcp/aqad099
  9. Wolfgang Dummer, Alexander Gaal, Thomas Sobottka, Fazel Ansari:
    »A Genetic Algorithm Approach for Medical Resident Scheduling in Austria«,
    Towards a Smart, Resilient and Sustainable Industry. ISIEA 2023 Lecture Notes in Networks and Systems, Band 745, Springer, Cham. https://doi.org/10.1007/978-3-031-38274-1_27
  10. Christoph Ecker, Martin Riester, Sebastian Schlund:
    »Duck Box: Sensor-Based Material Flow Optimization for Economically and Energy-efficient Intralogistics«,
    12th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS 2023), Seite 113-120
  11. Christoph Ecker, Matthias Hayek, Martin Riester, Wilfried Sihn:
    »Conceptual Design of a Decision Support System for Material Flow Planning and its Transfer to Public Transport«,
    Schriftenreihe der Wissenschaftlichen Gesellschaft für Arbeits- und Betriebsorganisation (WGAB) e. V., 2023, Seite 13-34, https://doi.org/10.30844/wgab_2023_2
  12. Gerhard Friedrich, Martin Gebser, Erich Teppan:
    »Symbolic Artificial Intelligence Methods for Prescriptive Analytics«,
    in: Vogel-Heuser, B., Wimmer, M. (eds) Digital Transformation. Springer Vieweg, Berlin, Heidelberg, Seite 385-414, https://doi.org/10.1007/978-3-662-65004-2_16
  13. Alexander Gaal, Wolfgang Dummer, Thomas Sobottka, Fazel Ansari, Sebastian Schlund:
    »Advancing Medical Resident Scheduling«,
    Schriftenreihe der Wissenschaftlichen Gesellschaft für Arbeits- und Betriebsorganisation (WGAB) e. V., 2023, Seite 115-134, https://doi.org/10.30844/wgab_2023_7
  14. Barna Gal, Viola Gallina, Ádám Szaller, Sebastian Schlund:
    »Optimization of a Remanufacturing Production Planning System with the Help of Artificial Intelligence«,
    in: Kohl, H., Seliger, G., Dietrich, F. (eds) Manufacturing Driving Circular Economy. GCSM 2022. Lecture Notes in Mechanical Engineering. Springer, Cham. , Seite 77-84, https://doi.org/10.1007/978-3-031-28839-5_9
  15. Viola Gallina, Barna Gal, Ádám Szaller, Daniel Bachlechner, Elisabeth Ilie-Zudor, Wilfried Sihn:
    »Reducing Remanufacturing Uncertainties with the Digital Product Passport«,
    in: Kohl, H., Seliger, G., Dietrich, F. (eds) Manufacturing Driving Circular Economy. GCSM 2022. Lecture Notes in Mechanical Engineering. Springer, Cham., Seite 60-67, https://doi.org/10.1007/978-3-031-28839-5_7
  16. Tarek A. Haila, Felix Schneider, Reimar Tausch, Martin Ritz, Pedro Santos, Dieter W. Fellner:
    »Color Calibration based on Mosaic Stitching of a Color Target as an Alternative to a Single-shot Approach«,
    Archiving Conference, 2023, Band 20, Seite 131-138, https://doi.org/10.2352/issn.2168-3204.2023.20.1.28
  17. Tarek A. Haila, Reimar Tausch, Martin Ritz, Pedro Santos, Dieter W. Fellner:
    »A cross-polarization as a possible cause for color shift in illumination«,
    Electronic Imaging, 2023, Seite 192-1–192-5,  https://doi.org/10.2352/EI.2023.35.15.COLOR-192
  18. Matthias Hayek, Gerald Mahringer, Roland Segner, Christian Landschütze, Wilfried Sihn:
    »Development of a Physical Internet container for an optimized wood supply chain«,
    Transportation Research Procedia, Band 72, 2023, Seiten 1950-1957, ISSN 2352-1465, https://doi.org/10.1016/j.trpro.2023.11.675
  19. Matthias Hayek, Mathias Nausch, Maximilian Peer, Tobias Walk, Martin Riester:
    »Öffi-Packerl - Konzept für eine synergetische Mobilität zur Abwicklung der letzten Meile in der Stadt der Zukunft«,
    Jahrbuch der Logistikforschung - Innovative Anwendungen, Konzepte & Technologien, Band 4, 2023, ISBN 978-3-99151-207-3
  20. Volker Knauthe, Thomas Pöllabauer, Katharina Faller, Maurice Kraus, Tristan Wirth, Max von Buelow, Arjan Kuijper, Dieter W. Fellner:
    »Distortion-Based Transparency Detection Using Deep Learning on a Novel Synthetic Image Dataset«,
    in: Image Analysis: 22nd Scandinavian Conference, SCIA 2023, Sirkka, Finland, Proceedings, Part I. Springer-Verlag, Berlin, Heidelberg, Seite 251–267, https://doi.org/10.1007/978-3-031-31435-3_17
  21. Nikolaus Kremslehner, Thomas Sobottka, Janos Nacsa, Richard Beregi, Sebastian Schlund:
    »Digital Twin training concept based on miniature demonstration factories«,
    Proceedings of the 13th Conference on Learning Factories (CLF 2023), http://dx.doi.org/10.2139/ssrn.4458212
  22. Hasan Kutlu, Felix Brucker, Ben Kallendrusch, Pedro Santos, Dieter W. Fellner:
    »AI-Based Image Segmentation of Cultural Heritage Objects used for Multi-View Stereo 3D Reconstructions«,
    in: GCH 2023, Eurographics Workshop on Graphics and Cultural Heritage, https://doi.org/10.2312/gch.20231160
  23. Kordula Lang-Illievich, Johanna Lang, Istvan-Szilard Szilagyi, Torsten Ullrich, Jolana Wagner-Skacel, Gabriela Repiska, Helmar Bornemann-Cimenti:
    »The Internet’s Interest in Autism Peaks in April: A Google Trends Analysis«,
    Journal of Autism and Developmental Disorders, 2023, Band 53, Seite 2915-2918, https://doi.org/10.1007/s10803-022-05614-y
  24. Lukas Lingitz, Viola Gallina, Johannes Breitschopf, Luana Finamore, Wilfried Sihn:
    »Quality in production planning: Definition, quantification and a machine learning based improvement method«,
    Procedia Computer Science, Band 217, 2023, Seite 358-365, ISSN 1877-0509, https://doi.org/10.1016/j.procs.2022.12.231
  25. Jonas A Müller, Viktoria A Krenn, Thomas Böni, Martin Haeusler:
    »The influence of lumbosacral transitional vertebrae on lumbar lordosis and the angle of pelvic incidence«,
    2023, Journal of Anatomy, https://doi.org/10.1111/joa.13985
  26. Martin Nocker, David Drexel, Michael Rader, Alessio Montuoro, Pascal Schöttle:
    »HE-MAN – Homomorphically Encrypted MAchine learning with oNnx models«,
    ICMLT '23: Proceedings of the 2023 8th International Conference on Machine Learning Technologies, 2023, Seite 35-45, https://doi.org/10.1145/3589883.3589889
  27. Christina Petschnigg, Alexander Pamler, Daniel Pfeiffer, Harald Urban, Guenter Koren, Torsten Ullrich:
    »Green space development monitoring for the smart city: a novel AI based methodology for the assessment of urban green«,
    Places and Technologies, 2023, ISBN: 978-86-7924-338-6
  28. Luisa Reichsthaler, Daniel Toth, Ádám Szaller, Wilfried Sihn:
    »A multi-criteria approach for assessing resilience, sustainability and efficiency measures in manufacturing companies«,
    Procedia CIRP, Band 120, 2023, Seite 547-552, ISSN 2212-8271, https://doi.org/10.1016/j.procir.2023.09.035
  29. Noël Scheder, Tim Teriete, Stefanie Eisl, Mathias Nausch, Markus Böhm:
    »Concept for value stream-oriented analyses of event-based data in three perspectives«,
    2023 International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT), Bengaluru, India, 2023, Seite 228-233, https://doi.org/10.1109/IDCIoT56793.2023.10053516
  30. Georg Schett, Alexandra Birkmaier, Martin Hrušovský, Vera Hemmelmayr:
    »Zweistufiges Planungsmodell zur Ermittlung des optimalen Güterwagenfuhrparks unter dynamischen Rahmenbedingungen«,
    Jahrbuch der Logistikforschung - Innovative Anwendungen, Konzepte & Technologien, Band 4, 2023, ISBN 978-3-99151-207-3
  31. Alexander Schmid, Alexander Granig, Thomas Sobottka, Martin Riester, Wilfried Sihn:
    »DISPO 4.0 | Simulationsbasierte Optimierung von Bestelllosgrößen, unter Prognoseunsicherheit in zwei Industrie-Fallbeispielen«,
    20. ASIM Fachtagung Simulation in Produktion und Logistik, Seite 423-432, https://doi.org/10.22032/dbt.57810
  32. Lennard Sielaff, Ruben Hetfleisch, Michael Rader:
    »Evaluation Framework for the Use of Privacy Preserving Technologies for Production Data«,
    Proceedings of the International Conference on Advanced Technologies, 2023, Seite 157-163, https://doi.org/10.58190/icat.2023.33
  33. Wilfried Sihn, Lisa Greimel:
    »Die instandhaltungsfreie Fabrik«,
    Instandhaltungsforum 2023, Tagungsband, Seite 1-6, DOI: 10.24406/publica-1035
  34. Thomas Sobottka, Felix Kamhuber:
    »Enhancing energy efficiency and flexibility for bakeries«,
    f2m: Sustainability and innovations supporting it ISBN: 978-3-9824079-5-1
  35. Daniel Ströter, Andreas Halm, Ulrich Krispel, Johannes S. Mueller-Roemer, Dieter W. Fellner:
    »Integrating GPU-Accelerated Tetrahedral Mesh Editing and Simulation«,
    in:  Wagner, G., Werner, F., Oren, T., De Rango, F. (Hrsg.) Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH) 2023, Lecture Notes in Networks and Systems, Springer, Cham, Band 601, Seite 24–42, https://doi.org/10.1007/978-3-031-23149-0_2
  36. Daniel Ströter, André Stork, Dieter W. Fellner:
    »Massively Parallel Adaptive Collapsing of Edges for Unstructured Tetrahedral Meshes«,
    in: High-Performance Graphics - Symposium Papers, The Eurographics Association, 2023, https://doi.org/10.2312/hpg.20231139
  37. Istvan-Szilard Szilagyi, Eva Eggeling, Helmar Bornemann-Cimenti, Torsten Ullrich:
    »Impact of the pandemic and its containment measures in Europe upon aspects of affective impairments: a Google Trends informetrics study«,
    Psychological Medicine, 2023, Band 53, Seite 7685-7697, https://doi.org/10.1017/S0033291723001563
  38. Patrick Taschner, Andreas Lehner, Wilfried Sihn:
    »Mechatronic gripper system and delivery platform for the autonomous cargo transport with unmanned aerial vehicles«,
    Transportation Research Procedia, 2023, Band 72, Seiten 1950-1957, ISSN 2352-1465, https://doi.org/10.1016/j.trpro.2023.11.325
  39. Sebastian Thiede, Antal Dér, Marc Münnich, Thomas Sobottka:
    »Manufacturing - Energy aspects in manufacturing system simulation – overview and case studies«,
    Springer Buch: Energy-Related Material Flow Simulation in Production and Logistics, Springer, Cham. https://doi.org/10.1007/978-3-031-34218-9_2
  40. Tristan Wirth, Arne Rak, Volker Knauthe, Dieter W. Fellner:
    »A Post Processing Technique to Automatically Remove Floater Artifacts in Neural Radiance Fields«,
    Computer Graphics Forum, 2023, Volume 42, https://doi.org/10.1111/cgf.14977
  41. Hendrik M. Würz, Kevin Kocon, Barbara Pedretscher, Eva Klien, Eva Eggeling:
    »A Scalable AI Training Platform for Remote Sensing Data«,
    AGILE: GIScience Series, 2023, Band 4, Seite 53, https://doi.org/10.5194/agile-giss-4-53-2023
  42. Daniel Zöttl, Christoph Ecker, Sebastian Lumetzberger, Sebastian Schlund:
    »Algorithm for optimizing truck utilization using residual capacities«,
    The 13th International Conference on Logistics & Transport 2023, Helsinki, Proceedings, Seite 32-41

  1.  F. Ansari, T. Madreiter, R. Glawar:
    »Knowledge-Based Maintenance«,
    in: Instandhaltungslogistik: Qualität und Produktivität steigern, Ausgabe 8, S. 305-333, ISBN 3446470093
  2. F. Ansari, L. Kohl:
    »AI-enhanced Maintenance for Building Resilience and Viability in Supply Chains«,
    in: Supply Network Dynamics and Control, DOI: 10.1007/978-3-031-09179-7_8
  3. D. Bachlechner, M. Rader, V. van Karsbergen, R. Pfluger:
    »Datenbasiert Energieverbrauch und Raumklima öffentlicher Gebäude verbessern – Literaturstudie mit Fokus auf den Erfolg von Ansätzen«,
    Bauphysik, 44, 5, S. 255 – 263
  4. U. Augsdörfer, T. Ullrich:
    »Innovative Informations- und Kommunikationstechniken im digitalen Gebäude- und Baumanagement«,
    Agile Digitalisierung im Baubetrieb, Springer Vieweg, Wiesbaden, https://doi.org/10.1007/978-3-658-34107-7_6
  5. T. Biegel, N. Jourdan, T. Madreiter, L. Kohl, S. Fahle, F. Ansari, B. Kuhlenkötter, J. Metternich:
    »Combining Process Monitoring with Text Mining for Anomaly Detection in Discrete Manufacturing«,
    in: Proceedings of the 12th Conference on Learning Factories (CLF 2022), https://ssrn.com/abstract=4073942
  6. L. Czarnetzki, F. Lächler, F. Kainz, C. Laflamme, D. Bachlechner:
    »Enabling Supervised Machine Learning for SMEs through Data Pooling«,
    KI2022 - 45th German Conference on AI, in: KI 2022: Advances in Artificial Intelligence, Springer Verlag
  7. G. da Col, F. del Ben, M. Bulfoni, M. Turetta, L. Gerratana, S. Bertozzi, A. P. Beltrami, D. Cesselli:
    »Image Analysis of Circulating Tumor Cells and Leukocytes Predicts Survival and Metastatic Pattern in Breast Cancer Patients«,
    Frontiers in Oncology, 12, 725318, https://doi.org/10.3389/fonc.2022.725318
  8. G. da Col, E. Eggeling, M. Hudelist, C. Schinko, C. Surtmann, E. Teppan:
    »Sensor-Based Moisture Prediction for Flat Roofs«,
    Frontiers in Artificial Intelligence and Applications, Vol. 351, S. 149 – 152, https://doi.org/10.3233/FAIA220073
  9. G. da Col, E. Teppan:
    »Industrial-size job shop scheduling with constraint programming«,
    Operations Research Perspectives, Vol. 9, 100249, https://doi.org/10.1016/j.orp.2022.100249
  10. G. Friedrich, E. Teppan:
    »Künstliche Intelligenz verstehen und nutzen – Eine Einführung zur Anwendung der Künstlichen Intelligenz«,
    Hrsg: Handels-, Industrie-, Handwerks-, Tourismus- und Landwirtschaftskammer Bozen
  11. E. Koh, M. Blumenschein, L. Shao, T. Schreck:
    »Reordering Sets of Parallel Coordinates Plots to Highlight Differences in Clusters«,
    EuroVis Workshop on Visual Analytics, https://doi.org/10.2312/eurova.20221080
  12. K. Lang-Illievich, J. Lang, I.-S. Szilagyi, T. Ullrich, J. Wagner-Skacel, G. Repiska, H. Bornemann-Cimenti:
    »The Internet’s Interest in Autism Peaks in April: A Google Trends Analysis«,
    Journal of Autism and Developmental Disorders, https://doi.org/10.1007/s10803-022-05614-y
  13. L. Lingitz, V. Gallina, J. Breitschopf, L. Finamore, W. Sihn:
    »Quality in production planning: Definition quantification and a machine learning based imprvement method«,
    4th International Conference on Industry 4.0 and Smart Manufacturing, Procedia Computer Science, 217, S. 358 – 365
  14. S. Nixdorf, F. Ansari, S. Schlund, M. Wolf Maria Ursula Hulla, M. Papa, S. Bardy, A. Kress, J. Rosemeyer:
    »Work-Based Learning in Manufacturing Industry: A Sector-Based Meta-Analysis«,
    International Association of Learning Factories
  15. M. Oberascher, A. Halm, T. Ullrich, R. Sitzenfrei:
    »Analysing the influence of different temporal resolutions of water consumption data for leakage detection and localisation«,
    European Geosciences Union, https://doi.org/10.5194/egusphere-egu22-7399
  16. F. Öhlinger, L. Greimel, R. Glawar, W. Sihn:
    »An approach for AI-based forecasting of maintenance orders for MRO scheduling«,
    IFAC MIM 2022, IFAC-Papers Online, 55, 10, S. 2312 – 2317
  17. R. Glawar, F. Ansari, L. Reichsthaler, W. Sihn, D. Toth:
    »Maintenance-Free Factory: A Holistic Approach for Enabling Sustainable Production Management«,
    in: IFAC-Papers Online, 55, 10, S. 2318 – 2323
  18. R. Glawar, K. Kovacs, T. Nemeth:
    »Innovative Trends und Technologien im Bereich Instandhaltungsplanung«,
    in: K. Matyas: Instandhaltungslogistik 8. Auflage
  19. M. Rathmair, T. Haspl, T. Komenda, B. Reiterer, M. Hofbaur:
    »A Formal Verification Approach for Robotic Workflows«,
    in: 20th International Conference on Advanced Robotics (ICAR), Ljubljana, S. 670 – 675
  20. N. Rodrigues, L. Shao, J. Jun Yan, T. Schreck, D. Weiskopf:
    »Eye Gaze on Scatterplot: Concept and First Results of Recommendations for Exploration of SPLOMs Using Implicit Data Selection«,
    ACM Symposium on Eye Tracking Research and Applications, https://doi.org/10.1145/3517031.3531165
  21. T. Rusch, M. Spitzhirn, S. Sen, T. Komenda:
    »Quantifying the economic and ergonomic potential of simulated HRC systems in the focus of demographic change and skilled labor shortage«,
    in: IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), Singapore, S. 1377 – 1381
  22. C. Schinko, L. Shao, J. Mueller-Roemer, D. Weber, X. Zhang, E. Lee, B. Sander, A. Steinhardt, V. Settgast, K. Chen, M. Erdt, E. Eggeling:
    »Accelerated Air-borne Virus Spread Simulation: Coupling Agent-based Modeling with GPU-accelerated Computational Fluid Dynamics«,
    International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, https://doi.org/10.5220/0000156800003124
  23. A. Schmid, T. Sobottka, W. Sihn:
    »DISPO 4.0 | Digitalization Of Inventory Calculation In Consumption-Based Material Planning In The Capital Goods Industry«,
    in: Proceedings of the Conference on Production Systems and Logistics - CPSL 2022, Vancouver (Canada), 17th-20th May 2022, S. 632-641
  24. A. Schmid, F. Kamhuber, T. Sobottka, W. Sihn:
    »DISPO 4.0 | Simulation-based optimization of stochastic demand calculation in consumption-based material planning in the capital goods industry«,
    in: MOTSP 2022 | 13th International Scientific Conference Management of Technology – Step to Sustainable Production, in: Tehnički glasnik, 16, 3, S. 333 – 340
  25. A. Schmid, F. Kamhuber, T. Sobottka, W. Sihn:
    »DISPO 4.0 I Simulationsgestützte Absatzprognose-optimierung in der Investitionsgüterindustrie«,
    ASIM 2022 - 26. Symposium Simulationstechnik, in: Proceedings Langbeiträge ASIM SST 2022, ARGESIM Report 20, ASIM Mitteilung 180, Wien, S. 25.-27
  26. A. Schmid, S. Luther, W. Sihn:
    »Demand Planning Falcon – Zielgenaue Bedarfsvorhersagen mit einer neu entwickelten digitalen Planungsmethode«, Zeitschrift "Industrie 4.0 Management«,
    Ausgabe 6, Seite 47-50
  27. A. Schmid, T. Sobottka, W. Sihn:
    »DISPO 4.0 | Digitalization Of Inventory Calculation In Consumption-Based Material Requirements Planning In The Capital Goods Industry«,
    3rd Conference on Production Systems and Logistics (CPSL 2022), in: Proceedings of the Conference on Production Systems and Logistics - CPSL 2022, 17.-20. Mai 2022, Vancouver, S. 632-641
  28. V. Settgast, K. Kostarakos, E. Eggeling, M. Hartbauer, T. Ullrich:
    »Product Tests in Virtual Reality: Lessons Learned during Collision Avoidance Development for Drones«,
    Designs, https://doi.org/10.3390/designs6020033
  29. T. Sobottka, F. Kamhuber:
    »Mehr Energieeffizienz und -flexibilität für Bäckereien«,
    Automatisierung – Forschung und Technologie; Eine Sonderedition von brot+backwaren
  30. I.-S. Szilagyi, G. A. Schittek, C. Klivinyi, H. Simonis, T. Ullrich, H. Bornemann-Cimenti:
    »Citation of retracted research: a case-controlled, ten-year follow-up scientometric analysis of Scott S. Reuben’s malpractice«,
    Scientometrics, https://doi.org/10.1007/s11192-022-04321-w
  31. E. Teppan:
    »Types of Flexible Job Shop Scheduling: A Constraint Programming Experiment«,
    International Conference on Agents and Artificial Intelligence, https://doi.org/10.5220/0010849900003116

  1. C. Altenhofen, T. Ewald, A. Stork, D. W. Fellner:
    »Analyzing and Improving the Parameterization Quality of Catmull-Clark Solids for Isogeometric Analysis«,
    in: IEEE Computer Graphics and Applications. Vol. 41, 3, 2021, S. 34–47
  2. F. Ansari, L. Kohl, J. Giner, H. Meier:
    »Text mining for AI enhanced failure detection and availability optimization in production systems«,
    CIRP Annals, Vol. 70, 1, 2021, S. 373–376
  3. A. Birkmaier, B. Oberegger, A. Felsberger, G. Reiner, W. Sihn:
    »Towards a robust digital production and logistics network by implementing flexibility measures«,
    Procedia CIRP, Vol. 104, 2021, S. 1310–1315
  4. M. Brandstötter, T. Komenda, G. Breitenhuber, M. Rathmair, M. Steiner, C. La Flamme, A. Müller, M. Hofbaur:
    »A method to enhance the flexibility of collaborative human-robot workspaces through an extended safety perspective«,
    15th CIRP Conference on Intelligent Computation in Manufacturing Engineering (ICME)
  5. I. Dimény, T. Koltai, C. Sepe, T. Murino, V. Gallina, T. Komenda:
    »MILP model to decrease the number of workers in assembly lines with human-robot collaboration«,
    IFAC-PapersOnLine, Vol. 54, 1, 2021, S. 169–174
  6. C. Ficher, S. Schlund:
    »Ansatz zur Integration biomechanischer Grenzwerte in Prozesssimulationen kollaborativer Mensch-Roboter-Arbeitssysteme«,
    67. Frühjahrskongress der Gesellschaft für Arbeitswissenschaft (GfA)
  7. V. Gallina, L. Lingitz, J. Breitschopf, E. Zudor, W. Sihn:
    »Work in Progress Level Prediction with Long Short-Term Memory Recurrent Neural Network«,
    Procedia Manufacturing, Vol. 54, 2021, S. 136–141
  8. J. Giner, R. Lamprecht, V. Gallina, C. Laflamme, L. Sielaff, W. Sihn:
    »Demonstrating Reinforcement Learning for Maintenance Scheduling in a Production Environment«,
    2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 2021, S. 1–8
  9. R. Glawar, F. Ansari, Z. Viharos, K. Matyas, W. Sihn:
    »Integrating maintenance strategies in autonomous production control using a cost-based model«,
    IMEKO ACTA Journal, Vol. 10, 3, 2021, S. 156–166 
  10. R. Glawar, F. Ansari, K. Matyas:
    »Evaluation of Economic Plausibility of Integrating Maintenance Strategies in Autonomous Production Control: A Case Study in Automotive Industry«,
    IFAC-PapersOnLine, Vol. 54, 1, 2021, S. 43–48 
  11. C. Halbwidl, T. Sobottka, A. Gaal, W. Sihn:
    »Deep Reinforcement Learning as an Optimization Method for the Configuration of Adaptable, Cell-Oriented Assembly Systems«;
    Procedia CIRP, Vol. 104, 2021, S. 1221–1226
  12. S. Hollerer, C. Fischer, B. Brenner, M. Papa, S. Schlund, W. Kastner, J. Fabini, T. Zselby:
    »Cobot attack: a security assessment exemplified by a specific collaborative robot«,
    Procedia Manufacturing, Vol. 54, 2021, S. 191–196
  13. Cs. Kardos, C. Laflamme, V. Gallina, W. Sihn:
    »Dynamic scheduling in a job-shop production system with reinforcememt learning«,
    Procedia CIRP, Vol. 97, 2021, S. 104–109
  14. S. Kloiber, V. Settgast, C. Schinko, M. Weinzerl, T. Schreck, R. Preiner: »A System for Collaborative Assembly Simulation and User Performance Analysis«, Proceedings of the International Conference on Cyberworlds, 2021, S. 93–100
  15. S. Kober, V. Settgast, M. Brunnhofer, U. Augsdörfer, G. Wood:
    »Move your virtual body: differences and similarities in brain activation patterns during hand movements in real world and virtual reality«,
    Virtual Reality, 2021, doi.org/10.1007/s10055-021-00588-1
  16. T. Komenda, M. Brandstötter, T. Gharagyozyan, A. Pichler, W. Liemberger:
    »Failure Prediction in Robotic Spot-Welding Applications - Challenges in Data Management«,
    15th CIRP Conference on Intelligent Computation in Manufacturing Engineering (ICME)
  17. T. Komenda, M. Brandstötter, S. Schlund:
    »A comparison of and critical review on cycle time estimation methods for human-robot work systems«,
    Procedia CIRP, Vol. 104, 2021, S. 1119–1124
  18. T. Komenda, M. Schelle, F. Kamhuber, S. Schlund:
    »Exploiting the potential of human-machine work systems - A hybrid cycle time determination model considering system parameters influencing cycle time«,
    19. ASIM Fachtagung Simulation in Produktion und Logistik
  19. T. Komenda, C. Schmidbauer, D. Kames, S. Schlund:
    »Learning to share - Teaching the impact of flexible task allocation in human-cobot teams«,
    Proceedings of the 11th Conference on Learning Factories (CLF), 2021
  20. K. Kovacs, F. Ansari, W. Sihn:
    »A modified Weibull model for service life prediction and spare parts forecast in heat treatment industry«,
    Procedia Manufacturing, Vol. 54, 2021, S. 172–177
  21. K. Kovacs, C. Heistracher, J. Giner, W. Sihn, J. Schneeweiss:
    »A multi-level model for realizing data-driven maintenance in manufacturing enterprises: Use case of jewelry production«,
    Procedia CIRP, Vol. 104, 2021, S. 1553–1558
  22. K. Kovacs, L. Reichthaler, M. Leitgeb-Waha, G. Unger:
    »Innovative Servicekonzepte durch prädiktive Instandhaltung«,
    ÖVIA
  23. H. Kutlu, M. Ritz, P. Santos, D. W. Fellner:
    »Fully Automatic Mechanical Scan Range Extension and Signal to Noise Optimization of a Lens-Shifted Structured Light System«,
    Proceedings of the Eurographics Workshop on Graphics and Cultural Heritage, 2021, S. 71–74
  24. F. Leber, J. B. Garcia, W. Wöber, T. Komenda, M. Aburaia, A. Aburaia:
    »Canonical Robot Command Language Plugin Framework«,
    Austrian Robotics Workshop 2021 (ARW)
  25. T. Madreiter, L. Kohl, F. Ansari:
    »A Text Understandability Approach for Improving Reliability-Centered Maintenance in Manufacturing Enterprises«,
    in: Dolgui A., Bernard A., Lemoine D., von Cieminski G., Romero D. (eds) Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems. APMS 2021. IFIP Advances in Information and Communication Technology, Vol. 630. Springer, Cham.
  26. W. Mayrhofer, S. Nixdorf, C. Fischer, T. Zigart, C. Schmidbauer, S. Schlund:
    »Learning Nuggets for Cobot Education: A Conceptual Framework, Implementation, and Evaluation of Adaptive Learning Content«,
    Proceedings of the 11th Conference on Learning Factories (CLF), 2021
  27. M. Nausch, P. Hold, W. Sihn:
    »A Methodological Approach for Monitoring Assembly Processes«,
    Procedia CIRP, Vol. 104, 2021, S. 1233–1238
  28. S. Nixdorf, F. Ansari, W. Sihn:
    »Work-Based Learning in Smart Manufacturing: Current State and Future Perspectives«;
    Proceedings of the Conference on Learning Factories (CLF), 2021
  29. M. Papa, S. Nixdorf, S. Schlund, D. Aschenbrenner:
    »Teaching Robotics: Description Model for Synergetic Combination of Robotics Learning Content«,
    Proceedings of the 11th Conference on Learning Factories (CLF), 2021
  30. D. Piacun, T. Ionescu, S. Schlund:
    »Crowdsourced Evaluation of Robot Programming Environments: Methodology and Application«,
    Applied Sciences, 2021, 11, 10903
  31. P. Rodler, E. Teppan, D. Jannach:
    »Randomized Problem-Relaxation Solving for Over-Constrained Schedules«,
    Proceedings of the International Conference on Principles of Knowledge Representation and Reasoning, Vol. 18, 2021, S. 696–701
  32. P. Rupprecht, H. Kueffner-McCauley, M. Trimmel, S. Schlund:
    »Adaptive Spatial Augmented Reality for Industrial Site Assembly«,
    Procedia CIRP, Vol. 104, 2021, S. 405–410
  33. P. Rupprecht, S. Schlund:
    »Taxonomy for Individualized and Adaptive Human-Centered Workplace Design in Industrial Site Assembly«,
    in: Russo D., Ahram T., Karwowski W., Di Bucchianico G., Taiar R. (eds) Intelligent Human Systems Integration 2021. IHSI 2021. Advances in Intelligent Systems and Computing, Vol. 1322, Springer, Cham.
  34. C. Schinko, T. Ullrich:
    »Vertex climax: Converting geometry into a non-manifold midsurface«,
    Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, Vol. 1, 2021, S. 185–192
  35. S. Schlund, C. Jandl, F. Taurer, M. Hartner-Tiefenthaler, M. Wagner, T. Moser:
    »Perceptions of Using Tracking and Tracing Systems in Work Environments«,
    Intermnational Conference on Human-Computer Interaction
  36. S. Schlund, H. Lovasz-Bukvova, M. Hölzl, G. Kormann-Hainzl, T. Moser, T. Zigart:
    »Usability and Task Load of Applications in Augmented and Virtual Reality«,
    European Conference on Software Process Improvement
  37. S. Schlund, C. Schmidbauer, T. Ionescu, B. Hader:
    »Adaptive Task Sharing in Human-Robot Interaction in Assembly«,
    2020 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), S. 546–550
  38. S. Schlund, C. Schmidbauer, B. Hader:
    »Evaluation of a Digital Worker Assistance System to enable Adaptive Task Sharing between Humans and Cobots in Manufacturing«,
    Procedia CIRP, Vol. 104, 2021, S. 38–43
  39. S. Schlund, M. Schmidt:
    »Robotic Process Automation in Industrial Engineering: Challenges and Future Perspectives«,
    in: Proceedings of the AHFE 2021 Virtual Conferences on Human Aspects of Advanced Manufacturing, Advanced Production Management and Process Control, and Additive Manufacturing, Modeling Systems and 3D Prototyping, 2021, USA S. 320–327
  40. A. Schmid, M. Lielacher, T. Sobottka, W. Sihn:
    »Dispo 4.0 -  Simulationsbasierte Optimierung von Bestelllosgrößen in der verbrauchsgesteuerten Materialdisposition der Investitionsgüterindustrie«,
    Simulation in Produktion und Logistik, Jörg Franke & Peter Schuderer (Hrsg.) Cuvillier Verlag, Göttingen 2021
  41. M. Steinlechner, A. Schumacher, B. Fuchs, L. Reichsthaler, S. Schlund:
    »A maturity model to assess digital employee competencies in industrial enterprises«,
    Procedia CIRP, Vol. 104, 2021, S. 1185–1190
  42. D. Ströter, U. Krispel, J. Mueller-Roemer, D. W. Fellner:
    »TEdit: A distributed tetrahedral mesh editor with immediate simulation feedback«,
    Proceedings of the International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH 2021), Vol. 11, 2021, S. 271–277
  43. I. S. Szilagyi, T. Ullrich, K. Lang-Illievich, C. Klivinyi, G. A. Schittek, H. Simonis, H. Bornemann-Cimenti:
    »Google trends for pain search terms in the world's most populated regions before and after the first recorded COVID-19 case: Infodemiological study«,
    Journal of Medical Internet Research, Vol. 23, 2021, e27214
  44. T. B. Tuli, L. Kohl, S. A. Chala, M. Manns, F. Ansari,
    »Knowledge-Based Digital Twin for Predicting Interactions in Human-Robot Collaboration«,
    2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 2021, S. 1–8
  45. T. Ullrich:
    »On the Autoregressive Time Series Model Using Real and Complex Analysis«,
    Forecasting, Vol. 3, 2021, S. 716–728
  46. T. Ullrich:
    »Real-world String Comparison: How to handle Unicode sequences correctly«,
    ACM Queue, Vol. 19, 2021, S. 107–116

  1. F. Ansari, P. Hold & M. Khobreh:  
    »A Knowledge-Based Approach for Representing Jobholder Profile toward Optimal Human-Machine Collaboration in Cyber Physical Production Systems«;  
    CIRP Journal of Manufacturing Science and Technology, Elsevier, Vol. 28 (2020), S. 87-106.
  2. F. Ansari:  
    »Cost-Based Text Understanding to Improve Maintenance Knowledge Intelligence in Manufacturing Enterprises, Computers and Industrial Engineering«;  
    Elsevier, Vol. 141 (2020). 
  3. F. Biebl, R. Glawar, F. Ansari, W. Sihn et al.:
    »A conceptual model to enable prescriptive maintenance for etching equipment in semiconductor manufacturing«;
    Procedia CIRP, 88 (2020), S. 64 - 69.
  4. A. Gaal, K. Hofer, T. Ryback, L. Lingitz, W. Sihn:
    »An agent-based approach to planning and controlling adaptable cell-oriented assembly systems«; 
    Procedia CIRP, 93 (2020), S. 1158 - 1163.
  5. R. Getto, A. Kuijper, D. W. Fellner: 
    »Automatic Procedural Model Generation for 3D Object Variation«; 
    The Visual Computer, 36(2020); S. 53-70.
  6. D. Kames, W. Mayrhofer, S. Schlund:
    »Made in Austria 2020: Einsatz von Assistenzsystemen in der österreichischen Industrie«;
    WINGbusiness, 53 (2020), 02; S. 6 - 11.
  7. C. Kardos, C. Laflamme, V. Gallina, W. Sihn: 
    »Dynamic scheduling in a job-shop production system with reinforcement learning«; 
    Procedia CIRP, 97(2020), S. 104-10
  8. F. Kamhuber, T. Sobottka, B. Heinzl, J. Henjes, W. Sihn: 
    »An efficient hybrid multi-criteria optimization approach for rolling production smoothing of a European food manufacturer«;
    Computers & Industrial Engineering, 147 (2020).
  9. S. Kloiber*, V. Settgast, Ch. Schinko, M. Weinzerl, J. Fritz, T. Schreck, R. Preiner: 
    »Immersive analysis of user motion in VR applications«;  
    The Visual Computer, 36 (2020); S. 1937-1949.
  10. W. Mayrhofer, D. Kames, S. Schlund:
    »Made In Austria 2019 - Survey Results Of The First Industry Panel On Production Work In Austria«;
    Management and Production Engineering Review, 11 (2020), 3; S. 4 - 13.
  11. J. S. Mueller-Roemer, A. Stork, D. Fellner:
    »Analysis of Schedule and Layout Tuning for Sparse Matrices With Compound Entries on GPUs«; Computer Graphics Forum, 39 (1.Sept.2020); S. 133-143.
  12. C. Schinko & T. Ullrich: 
    »A new grid-based midsurface generation algorithm«; Hyperseeing – the Publication of the International Society of the Arts, Mathematics, and Architecture, 2020, 19:81-84.
  13. C. Schmidbauer, T. Komenda, S. Schlund:
    »Teaching Cobots in Learning Factories - User and Usability-Driven Implications«;
    Procedia Manufacturing, 45 (2020), 7 S.
  14. A. Schumacher, W. Sihn: 
    »A Strategy Guidance Model to realize Industrial Digitalization in Production Companies«; 
    Management and Production Engineering Review, 11 (2020), 3; S. 14 - 25.
  15. A. Schumacher, W. Sihn: 
    »Development of a Monitoring System for Implementation of Industrial Digitalization and Automation using 143 Key Performance Indicators«; 
    Procedia CIRP, 93 (2020), S. 1310 - 1315.
  16. T. Sobottka, F. Kamhuber, B. Heinzl: 
    »Simulation-Based Multi-Criteria Optimization of Parallel Heat Treatment Furnaces at a Casting Manufacturer«; 
    Journal of Manufacturing and Materials Processing, 4 (2020), 3. 
  17. D. Ströter, J. Mueller-Roemer, A. Stork, D. W. Fellner 
    »OLBVH: octree linear bounding volume hierarchy for volumetric meshes«; 
    The Visual Computer, 36(2020); S. 2327-2340. 
  18. R. Tausch, M. Domajnko, M. Ritz, M. Knuth, P. Santos, D. Fellner: 
    »Towards 3D Digitization in the GLAM (Galleries, Libraries, Archives, and Museums) Sector - Lessons Learned and Future Outlook«; 
    IPSI Transactions on Internet Research, 16 (2020); S. 45-53. 
  19. M. Ulrich, D. Bachlechner: 
    »Wirtschaftliche Bewertung von KI in der Praxis – Status Quo, methodische Ansätze und Handlungsempfehlungen«; 
    HMD Praxis der Wirtschaftsinformatik, 57 (2020); S. 46-59.

  1. F. Ansari, R. Glawar, T. Nemeth:
    »PriMa: a prescriptive maintenance model for cyber-physical production systems«;
    International Journal of Computer Integrated Manufacturing, 32 (2019), 4-5; S. 482 - 503.
  2. R. Glawar, F. Ansari, C. Kardos, K. Matyas, W. Sihn:
    »Conceptual Design of an Integrated Autonomous Production Control Model in association with a Prescriptive Maintenance Model (PriMa)«;
    Procedia CIRP, 80 (2019), S. 482 - 487.
  3. M. Hennig, G. Reisinger, T. Trautner, P. Hold, D. Gerhard, A. Mazak:
    »TU Wien Pilot Factory Industry 4.0«;
    Procedia Manufacturing, 31 (2019), S. 200 - 205. 
  4. T. Ionescu, S. Schlund:
    »A Participatory Programming Model for Democratizing Cobot Technology in Public and Industrial Fablabs«;
    Procedia CIRP, 81 (2019), S. 93 – 98.
  5. M. Karner, R. Glawar, W. Sihn, K. Matyas:
    »An industry-oriented approach for machine condition-based production scheduling«;
    Procedia CIRP, 81 (2019), S. 938 - 943.
  6. T. Komenda, G. Reisinger, W. Sihn:
    »A Practical Approach of Teaching Digitalization and Safety Strategies in Cyber-Physical Production Systems«;
    Procedia Manufacturing, 31 (2019), S. 296 - 301.
  7. T. H. Luu, C. Altenhofen, T. Ewald, A. Stork, D. W. Fellner:
    »Efficient slicing of Catmull-Clark solids for 3D printed objects with functionally graded material«;
    Computers & Graphics, 82 (2019), S. 295 - 303.
  8. A. Mukhopadhyay, D. Kügler, A. Bucher, D. W. Fellner, T. Vogl: 
    »Putting Trust First in the Translation of AI for Healthcare«;
    ERCIM news, 116 (2019), S. 20 - 22.
  9. T. Nemeth, F. Ansari, W. Sihn:
    »A Maturity Assessment Procedure Model for realizing Knowledge- Based Maintenance Strategies in Smart Manufacturing Enterprises«;
    Procedia Manufacturing, 39 (2019), S. 645 - 654.
  10. T. Nemeth, F. Ansari, W. Sihn:
    »Industrielle Realisierung wissensbasierter Instandhaltungsstrategien - Ein instandhaltungsspezifisches Reifegradmodell für Produktionsunternehmen am Weg zur Smart Factory«;
    Industrie 4.0 Management, 5 (2019), S. 17 - 20.
  11. K. Ott, H. Pascher, W. Sihn:
    »Improving sustainability and cost efficiency for spare part allocation strategies by utilisation of additive manufacturing technologies«;
    Procedia Manufacturing, 33 (2019), S. 123 - 130.
  12. M. Ritz, S. Breitfelder, P. Santos, A. Kuijper, D. W. Fellner:
    »Seamless and non-repetitive 4D texture variation synthesis and real-time rendering for measured optical material behavior«;
    Computational Visual Media, vol. 5, 2 (2019), S. 161 - 170.
  13. T. Sobottka, F. Kamhuber, M. Faezirad, W. Sihn:
    »Potential for machine learning in optimized production planning with hybrid simulation«;
    Procedia Manufacturing, 39 (2019), S. 1844 - 1853.
  14. A. Stockert, R. Glawar, F. Ansari, W. Sihn:
    »Qualitätsprognose anhand Prozessparametern einer Papiermaschine mittels Industrial Data Science«;
    ZWF Zeitschrift für wirtschaftlichen Fabrikbetrieb, 114 (2019), 5; S. 310 - 313.

  1. F. Ansari, S. Erol, W. Sihn:
    »Rethinking Human-Machine Lear ning in Industry 4.0: How Does the Paradigm Shift Treat the Role of Human Learning?«;
    Procedia Manufacturing, 23 (2018), S. 117 - 122.
  2. F. Ansari, P. Hold, W. Sihn:
    »Human-Centered Cyber Physical Production System: How Does Industry 4.0 impact on Decision-Making Tasks?«;
    IEEE Technology and Engineering Managment Conference (TEMSCON), Oktober 2018 (2018), 6 S.
  3. F. Ansari, M. Khobreh, U. Seidenberg, W. Sihn:
    »A problem-solving ontology for human-centered cyber physical production systems«;
    CIRP Journal of Manufacturing Science and Technology, 22 (2018), S. 91 - 106.
  4. S. Chala, F. Ansari et al.:
    »Semantic matching of job seeker to vacancy: a bidirectional approach«;
    International Journal of Manpower, 39 (2018), 8; S. 1047 - 1063.
  5. R. Glawar, M. Karner, T. Nemeth, K. Matyas, W. Sihn:
    »An approach for the integration of anticipative maintenance strategies within a production planning and control model«;
    Procedia CIRP, 67 (2018), 6 S.
  6. R. Glawar, Z. Kemeny:
    »EPIC- Kompetenzschmiede im Donauraum«;
    Info Europa - Informationen über den Donauraum und Mitteleuropa (eingeladen), 1 (2018), S. 10 - 11.
  7. Z. Kemeny, R. Beregi, J. Nacsa, R. Glawar, W. Sihn:
    »Expanding production perspectives by collaborating learning factories-perceived needs and possibilities«;
    Procedia Manufacturing, 23 (2018), S. 111 - 116.
  8. U. Krispel, D. Fellner, T. Ullrich:
    »A Benchmark for Distance Measurements«;
    International Conference on Cyberworlds 2018. S. 120-125
  9. W. Kritzinger, A. Steinwender, S. Lumetzberger, W. Sihn:
    »Impacts of Additive Manufacturing in Value Creation System«;
    Procedia CIRP, 72 (2018), S. 1518 - 1523.
  10. L. Lingitz, V. Gallina, F. Ansari, W. Sihn et al.:
    »Lead Time Prediction using Machine Learning Algorithms: A Case Study by a Semiconductor Manufacturer«;
    Procedia CIRP, 72 (2018), S. 1051 - 1056.
  11. T. Nemeth, F. Ansari, W. Sihn et al.:
    »PriMa-X: A reference model for realizing prescriptive maintenance and assessing its maturity enhanced by machine learning«;
    Procedia CIRP, 72 (2018), S. 1039 - 1044.
  12. G. Reisinger, T. Komenda, P. Hold, W. Sihn:
    »A Concept towards Automated Data-Driven Reconfiguration of Digital Assistance Systems«;
    Procedia Manufacturing, 23 (2018), S. 99 - 104.
  13. W. Sihn, T. Sobottka, B. Heinzl, F. Kamhuber:
    »Interdisciplinary multi-criteria optimization using hybrid simulation to pursue energy efficiency through production planning«;
    CIRP Annals-Manufacturing Technology, 67 (2018), 1; S. 447 - 450.
  14. T. Sobottka, F. Kamhuber, M. Rössler, W. Sihn:
    »Hybrid simulation -based optimization of discrete parts manufacturing to increase energy efficiency and productivity«;
    Procedia Manufacturing, 21 (2018), S. 413 - 420.
  15. D. Weihrauch, P. Schindler, W. Sihn:
    »A conceptual model for developing a smart process control system«;
    Procedia CIRP, 67 (2018), 6 S.

  1. E. Abele, G. Chryssolouris, W. Sihn et al.:
    »Learning factories for future oriented research and education in manufacturing«;
    CIRP Annals-Manufacturing Technology, 66 (2017), S. 803 - 826.
  2. T. Arndt, G. Lanza, C. Lemmerer, C. Biegler, W. Sihn:
    »Steuerung globaler Produktionsnetzwerke«;
    wt Werkstattstechnik online, 107 (2017), 4; 6 S.
  3. S. Erol:
    »Recalling the rationale of change from process model revision comparison - a change-pattern based approach«;
    Computers in Industry, 87 (2017), C; S. 52 - 67.
  4. U. Krispel, T. Ullrich, M. Tamke:
    »Colored Point Clouds from In-built Cameras: Automated Colouring of Walls, Ceilings and Floors«;
    GIM international, 31, 10, S. 33-35
  5. C. Schinko, U. Krispel, E. Eggeling, T. Ullrich:
    »3D Model Representations and Transformations in the Context of Computer-Aided Design: a State-of-the-Art Overview«;
    Proceedings of the International Conference on Advances in Multimedia. S. 10-15
  6. T. Sobottka, F. Kamhuber, W. Sihn:
    »Energieeffizienz mittels optimierender Produktionsplanung und -steuerung«;
    ZWF Zeitschrift für wirtschaftlichen Fabrikbetrieb, Jahrg. 112 (2017), 9; S. 559 - 562.