Now showing 1 - 10 of 15
  • Publication
    Augmented learning for industrial education
    ( 2020)
    Menn, Jan Philipp
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    Severengiz, Mustafa
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    Lorenz, Andrea Katherija
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    Wassermann, Jonas
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    Ulbrich, Carsten
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    Seliger, Günther
    An efficient learning environment is required to cope with today's increasing innovation speed. Companies need methods and tools to transfer knowledge to employees in a fast way. Learners' cognitive focus should be shifted towards learning at the learning object, instead of transferring information from teaching material to the real world. Current learning environments are mostly incapable to merge physical learning tools with digital content at its point of use; therefore, the learner has to do it. Augmented reality offers the opportunity to show learning content directly on physical objects and to interact with it. Within this paper, two approaches on how to use augmented reality for teaching purposes are shown. One is for special machinery assembly of turbomachinery and the other for cocoa liquor production.
  • Publication
    Decentralised identification of used exchange parts with a mobile application
    Sustainable product development and use requires an extended life cycle of used and defective mechanical parts. Remanufacturing saves resources and helps the industry to utilise the product more efficiently. Reverse logistics is one of the most important challenges towards efficient remanufacturing. To improve this process, we propose an on-site part identification at the workshops. A fast on-site identification is essential for assisting repair shop personnel and saving time on searching for the right spare parts. Based on images taken by a mobile device our application provides various machine vision services, e.g., visual identification of used parts, already successfully tested in a sorting facility for remanufacturing parts. The mobile application provides a robust visual identification for different environments. We show that enhancing data for machine vision approaches with images from decentral sensors, i.e., mobile devices, leads to an improved identification accuracy.
  • Publication
    Serious Game on Factory Planning for Higher Education
    ( 2020)
    Severengiz, Mustafa
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    Seliger, Günther
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    Research has shown that student-centered classes are a promising approach to enhance learning. Even though this is well known, classes are often still designed in teacher-centered classes like lectures. However, lectures do not promote desired higher cognitive levels, which are needed for tackling the complex, all-embracing sustainability challenge. One promising approach to go for these higher levels is the usage of serious games. In this paper Factory Planner, a serious game on the VDI 5200 regarding factory planning, is presented. Factory Planner is a board game enhanced by an application. The game was evaluated with a pre- and post-game test measuring the knowledge gains at a bachelor's class. Further, a survey filled out by the students was conducted, which indicates a positive effect of Factory Planner on addressed learning goals and on students' motivation towards factory planning.
  • Publication
    Roboterprogrammierung vereinfachen
    Roboterprogrammierung ist trotz allen Weiterentwicklungen in der Steuerungstechnik und Mensch-Maschine-Interaktion immer noch ein kompliziertes Problem und dementsprechend kostspielig. Gerade in kleinen und mittelständischen Unternehmen stehen daher dem Robotereinsatz hohe Hürden gegenüber. Dieser Artikel befasst sich mit Möglichkeiten die Roboterprogrammierung - unter Zuhilfenahme von verschiedenen erweiterten Realitäten - zu vereinfachen und zu beschleunigen.
  • Publication
    Design alternatives for internationally distributed learning factories in global production engineering
    ( 2020)
    Schumacher, Bastian C.
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    Steinbach, Anja
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    Vi, Nguyen H.
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    Yükseltürk, Ahmet
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    ; ;
    Quoc, Huy Nguyen
    An internationally distributed learning factory (IDLF) provides opportunities to make students aware of intercultural challenges in global production networks. An IDLF is a scalable network of learning factories with value creation processes in spatially distributed locations. It enables collaboration and competition between student groups in distant locations and considers manual and automatic process methods. Due to the high number of design alternatives for IDLFs, a systematic approach for describing attractive characteristics is required. This paper shows design alternatives for IDLFs structural and process organization on the example of learning factories in Germany, Turkey and Vietnam.
  • Publication
    Deep learning for part identification based on inherent features
    The identification of parts is essential for the efficient automation of logistic processes such as part supply in assembly and disassembly. This paper describes a new method for the optical identification of parts without explicit codes but based on inherent geometrical features with Deep Learning. The paper focusses on the improvement of training of Deep Learning systems taking into account conflicting factors such as limited training data and high variety of parts. Based on a case study in turbine industry the effects of steadily growing training data on the robustness of part classification are evaluated.
  • Publication
    Enabling Human-Robot-Interaction via Virtual and Augmented Reality in Distributed Control Systems
    Production and assembly lines are nowadays transforming into flexible and interconnected cells due to rapidly changing production demands. Changes are, for example, varying locations and poses for the processed work pieces and tools as well as the involved machinery like industrial robots. Even a variation in the combination or sequence of different production steps is possible. In case of older involved machines the task of reconfiguration and calibration can be time consuming. This may lead, in addition with the expected upcoming shortage of highly skilled workers, to future challenges, especially for small and medium sized enterprises. One possibility to address these challenges is to use distributed or cloud-based control for the participating machines. These approaches allow the use of more sophisticated and therefore in most cases computationally heavier algorithms than offered by classic monolithic controls. Those algorithms range from simple visual servoing applications to more complex scenarios, like sampling-based path planning in a previously 3D-reconstructed robot cell. Moving the computation of the machine's reactions physically and logically away from the machine control complicates the supervision and verification of the computed robot paths and trajectories. This poses a potential threat to the machine's operator since he/she is hardly capable of predicting or controlling the robot's movements. To overcome this drawback, this paper presents a system which allows the user to interact with industrial robot and other cyber physical systems via augmented and virtual reality. Captured topics in this paper are the architecture and concept for the distributed system, first implementation details and promising results obtained by using a Microsoft HoloLens and other visualization devices.
  • Publication
    Registration of pre- and postoperative surface scans for pediatric neurosurgery
    ( 2018)
    Katanacho, Manuel
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    Lack, John-Certus
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    A software for automatic registration and differential visualization of pre- and postoperative surface scans for use in pediatric neurosurgery is developed and implemented. The core operations of the registration include an automatic head extraction, a rough registration by aligning the main axes, a depth map-based registration for robust determination and registration of feature points in the facial area, and a fine registration. A graphical user interface is implemented for the difference visualization and program control.
  • Publication
    Affordance Based Approach to Automatic Program Generation for Industrial Robots in Manufacturing
    Due to the increasing demand for flexible and low-cost production, manufacturing solutions involving human robot interaction have become much sought-after. Robotic manufacturers meet the demand with a rising number of low cost robots specifically designed around safety and usability. However, the programming is still based on a tool centric teach-in. This paper discusses an affordance based approach for process programming in industrial manufacturing. Using low level feature detection and a consecutive evaluation, a fast programming method for industrial applications is presented. The paper presents the concept and a prototypic implementation for a welding process. Using the affordance detection, the system is able to identify relevant seams based on an image of the work space. The identified seams are then presented to the user for review with the means of augmented reality. Lastly, the system derives a welding program based on the detected seams. First experiments show promising results concerning programming speed and path accuracy for different work piece shapes and task definitions. Finally, based on the experience gained with the prototype, the outlook discusses the possibilities and further fields for future work.
  • Publication
    CareJack - die intelligente Softorthese zur Ergonomieunterstützung
    Stressful physical activities are main reason for back pain, shoulder lesions and disc damage. These are the three main reasons for disability. ""CareJack"", a smart soft orthosis presented in this article, represents a novel approach to improve the workplace situation through automated real-time ergonomic analysis and assessment in order to indicate unergonomic movements or body poses to the user. The system is based on integrated movement measurement sensors, intelligent real-time movement data analysis algorithms and an embedded vibration feedback module.