Wissenschaftliche Publikationen

  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. 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
  5. 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
  6. 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 
  7. 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
  8. Vol. 54, 1, 2021, S. 43–48 
  9. 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
  10. 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
  11. Cs. Kardos, C. Laflamme, V. Gallina, W. Sihn: »Dynamic scheduling in a job-shop production system with reinforcememt learning«, Procedia CIRP
  12. Vol. 97, 2021, S. 104–109
  13. 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
  14. 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)
  15. 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
  16. 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
  17. K. Kovacs, L. Reichthaler, M. Leitgeb-Waha, G. Unger: »Innovative Servicekonzepte durch prädiktive Instandhaltung«, ÖVIA
  18. 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
  19. 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
  20. M. Nausch, P. Hold, W. Sihn: »A Methodological Approach for Monitoring Assembly Processes«, Procedia CIRP, Vol. 104, 2021, S. 1233–1238
  21. 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
  22. D. Piacun, T. Ionescu, S. Schlund: »Crowdsourced Evaluation of Robot Programming Environments: Methodology and Application«, Applied Sciences, 2021, 11, 10903
  23. P. Rupprecht, H. Kueffner-McCauley, M. Trimmel, S. Schlund: »Adaptive Spatial Augmented Reality for Industrial Site Assembly«, Procedia CIRP
  24. Vol. 104, 2021, S. 405–410
  25. 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
  26. 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
  27. 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
  28. T. Ullrich: »On the Autoregressive Time Series Model Using Real and Complex Analysis«, Forecasting, Vol. 3, 2021, S. 716–728
  29. T. Ullrich: »Real-world String Comparison: How to handle Unicode sequences correctly«, ACM Queue, Vol. 19, 2021, S. 107–116
  30. 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)
  31. C. Ficher, S. Schlund: »Ansatz zur Integration biomechanischer Grenzwerte in Prozesssimulationen kollaborativer Mensch-Roboter-Arbeitssysteme«, 67. Frühjahrskongress der Gesellschaft für Arbeitswissenschaft (GfA)
  32. 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
  33. 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
  34. 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
  35. 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
  36. 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
  37. F. Leber, J. B. Garcia, W. Wöber, T. Komenda, M. Aburaia, A. Aburaia: »Canonical Robot Command Language Plugin Framework«, Austrian Robotics Workshop 2021 (ARW)
  38. 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.
  39. 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
  40. 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
  41. 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.
  42. 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
  43. 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
  44. 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
  45. 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
  46. 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
  47. 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
  48. 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
  49. 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
  50. 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

  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.

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.

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.

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.

T. Ionescu, S. Schlund:
"A Participatory Programming Model for Democratizing Cobot Technology in Public and Industrial Fablabs";
Procedia CIRP, 81 (2019), S. 93 – 98.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.