Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK

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  • Publication
    PowerGrasp - Design and evaluation of a modular soft-robotic arm exosuit for industrial applications
    ( 2020)
    Goppold, Jean-Paul
    ;
    Kuschan, Jan
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    Thiele, Gregor
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    Schmidt, H.
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    Krüger, Jörg
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    Hackbart, R.
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    Kostelnik, J.
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    Liebach, J.
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    Wolschke, M.
    Absence from work caused by overloading the musculoskeletal system lowers the life quality of the worker and gains unnecessary costs for both the employer and the health system. Classical (rigid link) body-worn exoskeletons can help to reduce critical loading but show many disadvantages, preventing exoskeletons from extensive use in industrial environment. The presented PowerGrasp system is a very robust modular softrobotic arm exosuit sting of robust fabric with embedded rubber tubes as pressure chambers and soft-electronics and who's design is capable to overcome the critical limiting factors of classical exoskeletons. By inflating the tubes via pressure-control valves, it is possible to vary the stiffness of the chambers, which can be effectively used to generate assisting forces and moments at human joints. By using a joint based pressure control, it is possible to decrease the physical demand of overhead working for the wearer. Although the system is designed for i ndustrial overhead assembly, it can also be used in rehabilitation, craftsmanship and construction due to its portable and stand-alone concept. For assessing the impact of the PowerGrasp system, the raise of about 50 percent was shown. Finally, an evaluation study of the overall system has been conducted, showing very high user acceptance and usability.
  • Publication
    Roboterprogrammierung vereinfachen
    ( 2020)
    Guhl, J.
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    Heimann, Oliver
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    Krüger, Jörg
    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
    Low-Cost Embedded Vision for Industrial Robots: A Modular End-of-Arm Concept
    ( 2020)
    Kroeger, Ole
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    Wollschläger, Felix
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    Krüger, Jörg
    In this work we present our first prototype of a modular, low-cost end-of-arm concept for industrial robot applications. The goal is a faster, more flexible and cost-effective alternative compared to current industrial solutions. We use an embedded single-board computer and three cameras as a sensor base for the new system. The scope of robot application is supposed to as wide as possible (e.g. object detection, bin picking, assembly tasks and quality control tasks). We discuss some industry and low-cost-hardware solutions, introduce our system and deliver a proof of concept. Furthermore we use the system to accomplish a vision based pick and place task.
  • 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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    Krüger, Jörg
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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
    System identification of a hysteresis-controlled pump system using SINDy
    ( 2020)
    Thiele, Gregor
    ;
    Fey, Arne
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    Sommer, David
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    Krüger, Jörg
    Hysteresis-controlled devices are widely used in industrial applications. For example, cooling devices usually contain a two-point controller, resulting in a nonlinear hybrid system with two discrete states. Dynamic models of systems are essential for optimizing such industrial supply technology. However, conventional system identification approaches can hardly handle hysteresis-controlled devices. Thus, the new identification method Sparse Identification of Nonlinear Dynamics (SINDy) is extended to consider hybrid systems. SINDy composes models from basis functions out of a customized library in a data-driven manner. For modeling systems that behave dependent on their own past as in the case of natural hysteresis, Ferenc Preisach introduced the relay hysteron as an elementary mathematical description. In this new method (SINDyHybrid), tailored basis functions in form of relay hysterons are added to the library which is used by SINDy. Experiments with a hysteresis controlled water basin show that this approach correctly identifies state transitions of hybrid systems and also succeeds in modeling the dynamics of the discrete system states. A novel proximity hysteron achieves the robustness of this method. The impacts of the sampling rate and the signal noise ratio of the measurement data are examined accordingly.
  • Publication
    Networked Visual Servoing as Use-Case for Cloud-based Industrial Robot Control
    ( 2020)
    Vick, Axel
    ;
    Krause, Christian
    ;
    Krüger, Jörg
    Nowadays production industry and smart factory is dealing with methods of optimal resource load balancing and new types of flexible service-oriented strategies. It is seen crucial to adapt quickly to changes in manufacturing processes and new products or even integrate new hardware faster than the competition. Flexibility and Scalability can be improved by exchanging only a certain part of hardware and software without the need of touching all the other components. In this paper we present a methodical approach towards a typical use case in modern industrial robotic systems. The system consists of hardware components from different manufacturers which can be controlled and monitored separately by remote services. Those services can be combined to complex applications and integrate value added services. We show the independence and capability of exchangeable added value services running either centralized, decentralized, locally or remote. The experiments demonstrate how a process is improve by simply adding another service according to the Plug-and-Play paradigm. The service ensures the conditions of a computer vision system component to keep the reliability of the overall system workflow. In addition it will be demonstrated how system components could be virtualized in container-based cloud environments to save required on-board resources of the robotic system while keeping the whole system communication secure. Finally, results will be presented for different intercommunication scenarios.
  • Publication
    Automated Optical Inspection Using Anomaly Detection and Unsupervised Defect Clustering
    ( 2020)
    Lehr, Jan
    ;
    Sargsyan, Arlik
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    Pape, Martin
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    Philipps, Jan
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    Krüger, Jörg
    Neural networks have proven to be extraordinarily successful in many computer vision applications. But the approaches used to train neural networks require large datasets of annotated images, which requires a solid amount of human time to prepare those datasets. To facilitate the adoption of machine learning based technologies in industrial computer vision applications, this paper presents a two-step unsupervised learning approach for anomaly detection with further defect clusterization. In the first stage, the defects are not explicitly learned, but are interpreted as an anomaly or novelty based on the dataset of defect-free samples. In a second stage, the anomalies detected in the first stage are clustered in unsupervised manner and classified into meaningful categories by experts with process knowledge (e.g. critical or non-critical defect). This paper presents a first small dataset containing one industrial object with a complex shape. The object is made of aluminiu m and is shown both free of defects and defective. Based on this, recommendations are given for an acquisition setup for a large, extensive dataset. Most of the existing papers are studying the approaches for uniform surface (texture) inspection. The specifics of this research is to identify defects on rigid bodies, which exhibit highly non uniform texture in the image. State of the art methods were evaluated and improved to increase the classification accuracy. With a fine-tuned ResNet-18 it was possible to achieve 100% accuracy for defective and defect-free images.
  • Publication
    Decentralised identification of used exchange parts with a mobile application
    ( 2020)
    Lehr, Jan
    ;
    Schlüter, Marian
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    Krüger, Jörg
    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
    Process data based Anomaly detection in distributed energy generation using Neural Networks
    ( 2020)
    Klein, Max
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    Thiele, Gregor
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    Fono, Adalbert
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    Khorsandi, Niloufar
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    Schade, David
    ;
    Krüger, Jörg
    The increasing share of renewable energies in the total energy supply includes a growing number of small, decentralized energy generation which also provides control energy. These decentralized stations are usually combined to a virtual power plant which takes over the monitoring and control of the individual participants via an Internet connection. This high degree of automation and the large number of frequently changing subscribers creates new challenges in terms of detecting anomalies. Quickly adaptable, variable and reliable methods of anomaly detection are required. This paper compares two approaches using Neural Networks (NN) with respect to their ability to detect anomalous behavior in real process data of a combined heat and power plant. In order to include process dynamics, one approach includes specifically engineered features, while the other approach uses Long-Short-Term-Memory (LSTM). Both approaches are able to detect rudimentary anomalies. For more demanding anomalies, the respective strengths and weaknesses of the two approaches become apparent.
  • Publication
    Serious Game on Factory Planning for Higher Education
    ( 2020)
    Severengiz, Mustafa
    ;
    Seliger, Günther
    ;
    Krüger, Jörg
    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.