The ultimate goal of any kind of quality control is to avoid defective parts. Technologies related to achieving this goal are summarized under the strategic topic of “Zero Defect Manufacturing”.

PROFACTOR is developing methods that generate information in addition to results coming from quality control. These data enable the closing of the feedback loop from quality control to the production process, thus reducing or eliminating reject parts.

The first step to generating the necessary data is a suitable sensor technology. For metallic as well as (carbon fiber) composite parts specific sensor systems have been developed, e.g. for surface inspection based on photometric stereo combined with physical models of the surface’s reflectance properties. For detecting defects inside of parts active thermography has been developed for various kinds of materials.

The interpretation of the incoming data is either done through conventional, grey-level or texture-based segmentation algorithms or – more recently – through methods based on “deep learning” that are suitable for semantic segmentation. For the actual implementation in industrial environments the lack of training data is addressed by “generative adversarial networks” that can synthesize large quantities of image data from a smaller set of samples.

Data acquired during quality control are then combined with models of the production processes. These models enable the user to keep the production within tolerance limits by proposing specific adjustments of the parameters, especially when setting up a process for new product variant. For processes with high-value parts, where complex re-work processes may exist, decision support tools have been developed that combine quality data with logistical part flow simulations to optimize the performance of the whole production line.

The quality control systems for surface inspection are often realized in the form of inspection robots, especially when a full surface scan needs to be done for parts of complex shape. The necessary tools for coverage and motion planning, for defect detection, for backprojection of defects onto 3D CAD models have been developed for this purpose.

Projects

The requirements for quality control, even for complex components, increase up to a 100% quality inspection. The inspection of parts of complex shape requires robotic solutions to move a sensor system in such a way that the whole surface of the part is covered. SPIRIT aims at the development of a s...+
Major parts - including the wings of the Airbus A 380 - are made of fiber-reinforced composites. During machining - e. g. drilling - the inhomogeneity of the material in the inner walls of the boreholes can lead to fraying and loosening. However, the quality of the boreholes is essential for the str...+
The INLINE project aims at the solution of key challenges to enable the implementation of a scalable manufacturing process for fuel cell systems. Current manufacturing processes rely on manual work that has substantial limits in terms of cycle times, costs and scalability. Developments will start wi...+
The factors of success in the context of the digital factory are the inclusion of human within the manufacturing process as well as the consideration of their individuality and experience. Assistive systems act an important role in this field. The challenges of a nearby collaboration of human and ro...+
Die automatische Prüfung von Composite-Bauteilen gewinnt sowohl  in der Automobilindustrie als auch in der Luftfahrt zunehmend an Bedeutung. Während es bei den Produktionsverfahren substantielle Fortschritte gegeben hat, wird die Prüfung immer noch manuell durchgeführt, nimmt aber 30-50 Prozent...+
Initial situation: Efficient production of carbon composite parts is an important topic for aerospace, automotive and other industries. In a draping process, carbon fibre textiles are shaped in order to produce parts with complex shape. This draping process results in complex deformation of carbon f...+
Holzfurnieroberflächen spielen als Leichtbau-Dekorteile für die Luftfahrtindustrie eine wichtige Rolle. Diese Oberflächen sind hochglänzend lackiert, deren Qualität wird im Rahmen der Abnahme von den Erstausrüstern (OEM) kritisch bewertet. Dabei werden Messgeräte eingesetzt, die Kennwerte üb...+
Non-destructive testing of components is an important auxiliary process step, not only in quality control but also in regular maintenance. The detection of cracks is currently done by using magnetic particle inspection, which is a decades-old, inefficient and ecologically undesirable process. There ...+
Machine vision in industrial quality control, e.g. in surface inspection, generates an enormous amount of data. These data are input for machine learning structures that reproduce human decision making. The setup and optimization of such machine learning structures in industrial environments require...+
The EU research project DARWIN aims to develop a robotic system with cognitive abilities, that include acting, learning and thinking. The robotic system also aims to develop an understanding of its environment together with the physical properties of the components to be handled. In order to underst...+

Publications

Alexander Walch, Christian Eitzinger, Werner Palfinger, Sebastian Beyer, Pauline Meyr-Heye; Reactive coverage planning for robotic NDT of complex parts; accepted for: European Conference on NDT 2018

Edwin Lughofer, Robert Pollak, Alexandru-Ciprian Zavoianu, Mahardhika Pratama, Pauline Meyer-Heye, Helmut Zörrer, Christian Eitzinger, Julia Haim, Thomas Radauer; Self-Adaptive Evolving Forecast Models with Incremental PLS Space Update for On-line Predicting Quality of Micro-fluidic Chips: Engineering Applications of Artificial Intelligence,Volume 68, February 2018, Pages 131–151, https://doi.org/10.1016/j.engappai.2017.11.001

Edwin Lughofer, Roland Richter, Ulrich Neissl, Wolfgang Heidl, Christian Eitzinger, Thomas Radauer; Explaining classifier decisions linguistically for stimulating and improving operators labeling behavior: Information Sciences, Volume 420, December 2017, Pages 16-36, https://doi.org/10.1016/j.ins.2017.08.012

Heidl, S. Thumfart, E. Lughofer, C. Eitzinger, E. P. Klement; Machine Learning Based Analysis of Gender Differences in Visual Inspection Decision Making, Information Sciences, Vol. 224, pages 62-76, DOI: 10.1016/j.ins.2012.09.054, Mar 2013

Dittrich, T. Riklin-Raviv, G. Kasprian, R. Donner, P.C.Brugger, D. Prayer, G. Langs; A Spatio-Temporal Latent Atlas for Semi-Supervised Learning of Fetal Brain Segmentations and Morphological Age Estimation, Accepted for publication in Medical Image Analysis, 2013

Elkharraz, S. Thumfart, D. Akay, C. Eitzinger, B. Henson; Tactile texture features corresponding to human affective responses. Submitted to IEEE Transactions on Affective Computing

Heidl, S. Thumfart, E. Lughofer, C. Eitzinger, E. P. Klement; Machine Learning Based Analysis of Gender Differences in Visual Inspection Decision Making,Information Sciences, accepted, pre-press DOI: 10.1016/j.ins.2012.09.054

Grünauer, S. Zambal, K. Bühler; „Detektion von Koronararterien: Das Beste aus zwei Welten“, Bildverarbeitung für die Medizin (BVM):pp. 269-273, 2011

van Beilen, H. B ult, R. Renken, M. Stieger, S. T humfart, F. Cornelissen, V. Kooijman; Effects of Visual Priming on Taste-Odor Interaction, PLoS ONE 6(9): e23857, 2011, doi:10.1371/journal.pone.0023857

Heidl, C. Eitzinger, M. Gyimesi, F. Breitenecker; Learning over Sets with Recurrent Neural Networks: An Empirical Categorization of Aggregation
Functions, Mathematics and Computers in Simulation 82(3), pp. 442-449, doi:10.1016/j.matcom.2010.10.018, Nov 2011

Thumfart, R. H.A.H. Jacobs, E. Lughofer, C. Eitzinger, F. W. Cornelissen, W. Groissboeck, R. Richter, “Modeling human aesthetic perception of visual textures “, ACM Transactions on Applied Perception, Volume 8, Issue 5, Nov. 2011, doi:10.1145/2043603.2043609

Heidl, C. Eitzinger, M. Gyimesi, F. Breitenecker; Learning over Sets with Recurrent Neural Networks: An Empirical Categorization of Aggregation Functions, Mathematics and Computers in Simulation, ISSN 0378-4754, 2010

Groissboeck, E. Lughofer, S. Thumfart; Associating Visual Textures with Human Perceptions using Genetic Algorithms, Information Sciences, vol. 180, issue 11, pp. 2065-2084, doi:10.1016/j.ins.2010.01.035, 2010

H.A.H. Jacobs, R. Renken, S. Thumfart, F. W. Cornelissen; Different Judgments about Visual Textures Invoke Different Eye Movement Patterns, Journal of Eye Movement Research, 3(4):2, pp. 1-13, 2010

Edwin Lughofer, Robert Pollak, Alexandru-Ciprian Zavoianu, Mahardhika Pratama, Pauline Meyer-Heye, Helmut Zörrer, Christian Eitzinger, Julia Haim, Thomas Radauer; Self-Adaptive Evolving Forecast Models with Incremental PLS Space Update for On-line Predicting Quality of Micro-fluidic Chips, Engineering Applications of Artificial Intelligence,Volume 68, February 2018, Pages 131–151, https://doi.org/10.1016/j.engappai.2017.11.001

Edwin Lughofer, Roland Richter, Ulrich Neissl, Wolfgang Heidl, Christian Eitzinger, Thomas Radauer; Explaining classifier decisions linguistically for stimulating and improving operators labeling behavior, Information Sciences, Volume 420, December 2017, Pages 16-36, https://doi.org/10.1016/j.ins.2017.08.012

Alexandru-Ciprian Zavoianu, Edwin Lughofer, Robert Pollak, Pauline Meyer-Heye, Christian Eitzinger, Thomas Radauer; Multi-Objective Knowledge-Based Strategy for Process Parameter Optimization in Micro-Fluidic Chip Production, 2017 IEEE Symposium Series on Computational Intelligence, accepted

Tran, C. Eitzinger; ThermoBot – autonomous robotic system for thermographic detection of cracks. Workshop Proceedings of IAS-13, 13th Intl.Conf.on Intelligent Autonomous Systems, Padova (Italy) July 15-19,2014, ISBN 978-88-95872-06-3, pp.391-391

Eitzinger, S. Akkaladevi; Dexterous Assembler Robot Working with Embodied Intelligence, Workshop Proceedings of IAS-13, 13th Intl.Conf.on Intelligent Autonomous Systems, Padova (Italy) July 15-19,2014, ISBN 978-88-95872-06-3, pp.393-393

Eitzinger, K. Zhou; VALERI – Validation of Advanced, Collaborative Robotics for Industrial Applications. Workshop Proceedings of IAS-13, 13th Intl.Conf.on Intelligent Autonomous Systems, Padova (Italy) July 15-19,2014, ISBN 978-88-95872-06-3, pp.392-392

Eitzinger, A. Baghbanpourasl, S. Zambal; Image Processing Issues in Scanning Inspection Robots. Workshop Proceedings of IAS-13, 13th Intl.Conf.on Intelligent Autonomous Systems, Padova (Italy) July 15-19,2014, ISBN 978-88-95872-06-3, pp.394-402

Traxler, P. Thanner, G. Mahler; Temporal analysis for implicit compensation of local variations of emission coefficient applied for laser induced crack checking, 12th International Conference on Quantitative Infrared Thermography, Bordeaux, France, 7th-11th July 2014

Dittrich, T. Riklin-Raviv, G. Kasprian, R. Donner, P.C.Brugger, D. Prayer, G. Langs. A Spatio; Temporal Latent Atlas for Semi-Supervised Learning of Fetal Brain Segmentations and Morphological Age Estimation, Medical Image Analysis, Vol. 18(1), pp. 9-21, January 2014.

Alexander Walch, Christian Eitzinger; A combined calibration of 2D and 3D sensors, Proceedings of the VISAPP. 9th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, Lisbon, Portugal, 5th-8th Jan. 2014

Traxler, P. Thanner, P. Meyer Heyer; Design of and practical experience with a thermographic crack checking system using laser heating, 11th European conference on NDT, 2014 10 09 Prag, ISBN: 978-80-214-5018-9 by Brno University of Technology, http://www.ndt.net/events/ECNDT2014/app/content/Paper/166_Traxler.pdf

Traxler; Unterdrückung des Emissionsgradeinflusses in der Laser angeregten Rissprüfung, Tagungsband der ÖGfTh (Österreichische Gesellschaft für Thermografie), 26.9.2014 Eugendorf/Austria

Walch, C. Eitzinger. A combined calibration of 2D and 3D sensors, Proceedings of the VISAPP. 9th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, Lisbon, Portugal, 5th-8th Jan. 2014

Heidl, S. Thumfart, and C. Eitzinger, Humans Differ; So Should Models. Systematic Differences Call for Per-Subject Modeling, ICAART 2012: Proceedings of the 4th Int. Conf. on Agents and Artificial Intelligence, pages 413-418, Vilamoura, Portugal, February 6th-8th, 2012

Heidl, S. Thumfart, E. Lughofer, C. Eitzinger, E. P. Klement; Classifier-based analysis of visual inspection: Gender differences in decision-making, Proc. of SMC 2010, IEEE Conference on Systems, Man and Cybernetics, pp. 113-120, Istanbul, Turkey, October 2010

Thumfart, J. Scharinger, C. Eitzinger; Pixel based Texture Mixing, Proc. of the 34th Workshop of the Austrian Association for Pattern Recognition, pp. 147-154, Zwettl, Austria, May 27-28th 2010

Henson, G. Elkharraz, S. Thumfart, D. Akay, C. Eitzinger; Machine vision approach to predicting affective properties of tactile textures, In Proceedings of the International Conference on Kansei Engineering and Emotion Research, KEER 2010, Paris, France, March 2- 4, ISBN 978-4-9905104-0-4, pp. 2261 – 2270, 2010.

Thumfart, W. Palfinger, M Stöger, C. Eitzinger; Accurate Fibre Orientation Measurement for Carbon Fibre Surfaces, accepted for presentation at CAIP 2013, York, UK, Aug 27-29th, 2013

Eitzinger, S.Ghidoni, E. Menegatti; ThermoBot: towards semi-autonomous, thermographic detection of crack, Proc. of the International Conference on Heating by Electromagnetic Source HES-13, pp. 461-468, Padua, May 21-24, 2013

Eitzinger, PROFACTOR, Steyr-Gleink, Österreich, G. Mahler, InfraTec, Dresden; Konzeption und Aufbau einer robotergestützten Plattform für optisch angeregte Wärmefluss-Thermografie. Presented at DGZFP, Thermographie-Kolloquium 2013, 26. – 27. September 2013, Leinfelden-Echterdingen

Traxler, PROFACTOR, Steyr-Gleink, Österreich, S. Koch, Institut Dr. Foerster, Reutlingen; Inline-Prüfung von warmgewalzten Stahlknüppeln mittels Wärmeflussthermographie, Presented at DGZFP, Thermographie-Kolloquium 2013, 26. – 27. September 2013, Leinfelden-Echterdingen

Thanner, G. Traxler, Design for Thermographic Crack Checking System using Laser Induced Heat Flux Technology, Presented at Factory Automation Conference 2012, Veszprem, Hungary, 21-22 May 2012 Proceedings of Factory Automation 2012, pages 122-125, Veszprem, Hungary

Thumfart, W. Palfinger, C. Eitzinger; Vision based sensors enabling automated production of composite material. In the Proc. of SAMPE / SEMAT 2012, Munich, May 24th – 25th, pp. 301 – 306, ISBN: 978-3-952 3565-6-2, 2012

Eitzinger, S. Thumfart: Optimizing Feature Calculation in Adaptive Machine Vision Systems, M. Sayed-Mouchaweh and E. Lughofer (eds.), Learning in Non-Stationary Environments: Methods and Applications, DOI 10.1007/978-1-4419-8020-5_13, Springer Science+Business Media New York 2012

S.Thumfart, PhD Thesis: Genetic Texture Synthesis. Johannes Kepler University Linz, Department of Computational Perception, Feb 2012

Dittrich; Ein Atlas der frühen Gehirnentwicklung. Published online at ORF Science, July 2013

Thanner: “Defect Avoidance, Machine-vision system catches defects in seamless steel tube production using linescan cameras and nearinfrared imaging“, Vision Systems Design (VSD) Magazin, 1.6. 2010

Wögerer, P. Thanner, G. Traxler: “Measurement of Material properties with Thermography“, FACTORY AUTOMATION 2011 Conference, Györ, Hungary, 24-26 May 2011

Wögerer, P. Thanner, G. Traxler: „Thermografic methods for online control for steel pipes“, FACTORY AUTOMATION 2011 Conference, Györ, Hungary, 24-26 May 2011

Petra Thanner „Mülltrennung mit Infrarottechnologie“, Newsletter E!AT aktuell, März 2010

Thumfart; “Pixel based Texture Mixing“, ÖAGM 2010 – 34th annual workshop of the Austrian Association for Pattern Recognition (AAPR) – Computer Vision in a Global Society, Zwettl, 28. Mai 2010

Thanner, W. Palfinger, “Qualitätssicherung von Carbonfaserteilen mit Bildverarbeitung
Handhabungstechnik – Der Schlüssel für eine automatisierte Herstellung von Composite-Bauteilen, Augsburg, 8. Juli 2010

Thanner, W. Palfinger, G. Traxler, “Wärmeflussauswertung für die induktiv angeregte Rissprüfung“, Thermografieforum Eugendorf, Eugendorf, 10. September 2010

Eitzinger; “Adaptive Produktion“, 25 Jahre Eureka, Linz, 7. Oktober 2010

Thanner; “EM80 – OIDIPUS, Optimized InGaAS Detectors for Imaging Applications and Industrial Spectroscopy“, 25 Jahre Eureka, Linz, 7. Oktober 2010

Heidl; “Classifier – based analysis of visual inspection: Gender differences in decision-making“, SMC2010, IEEE International Conference on Systems, Man and Cybernetics, Istanbul, 11. Oktober 2010

Thanner, G. Traxler; “Advanced Evaluation for Thermographic Crack Detection with Inductive Excitation for Steele Billets“, 20th Manufuturing Confernece, Budapest, 20. Oktober 2010

Traxler; „Automatisierte Inline-Prüfmöglichkeit mit aktiver Thermographie“, Seminar Wärmefluss-Thermographie, Erlangen, 4. November 2010

Petra Thanner; Defect Avoidance, Machine-vision system catches defects in seamless steel tube production using linescan cameras and near-infrared imaging,Vision Systems Design (VSD) Magazi, 1.6. 2010

Thanner, G. Traxler; Qualitätssicherung von Carbonfaserteilen mittels Bildverarbeitung, 8. Juli 2010, Handhabungstechnik – Der Schlüssel für eine automatisierte Herstellung von Composite-Bauteilen, Augsburg, Germany

Your Contact

Dr. Christian Eitzinger
Head of Machine Vision

+43 7252 885 250
christian.eitzinger@nullprofactor.at

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