Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK

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  • Publication
    Green incremental learning - Energy efficient ramp-up for AI-enhanced part recognition in reverse logistics
    ( 2023)
    Schlüter, Marian
    ;
    Schimanek, Robert
    ;
    Koch, Paul
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    Briese, Clemens
    ;
    Chavan, Vivek Prabhakar
    ;
    Bilge, Pinar
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    Dietrich, Franz
    ;
    Krüger, Jörg
    Artificial Intelligence (AI) has made significant progress in supporting circular economy and reverse logistics by learning from diverse data to predict, e.g., routes or to assist workers in sorting. However, it remains an open question how AI can be integrated and trained into such operational processes, where little to no data has been collected previously. Traditionally, AI models would only be rated by their accuracy. This paper aims to introduce the concept of green incremental learning, i.e. rating AI models not only for their accuracy but to evaluate energy efficiency as well. A ramp-up of a data-driven AI system for part recognition is explored under consideration of energy efficiency. Therefore, we combine online and incremental learning, working with growing data sets to simulate a ramp-up phase. We present experiments of incremental learning on business and image data, partially supported by regular joint training steps. We start local CPU-based machine learning and prediction on business data from the first sample. Finally, we compare incremental learning to traditional batch learning and show energy-saving potential of up to 62 % without a significant drop in accuracy.
  • Publication
    Industrielle kraftgeregelte Schraubprozesse
    ( 2022)
    Bastidas Cruz, Arturo
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    Jaya, Tanureza
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    Haninger, Kevin
    ;
    Krüger, Jörg
    Manuelle Schraubmontagen profitieren von menschlichen feinmotorischen Fähigkeiten für die flexible Positionierung der Werkzeuge und Bauteile. Solche Prozesse lassen sich mithilfe eines kooperativen Robotersystems automatisieren, welches flexibel in einer dynamischen Umgebung agiert und insbesondere die Fähigkeit mitbringt, hohe Prozesskräfte aufzunehmen. In diesem Beitrag wird eine Methode zur Automatisierung von kraftgeregelten Schraubvorgängen beschrieben und die sich dabei ergebenden Herausforderungen erläutert.
  • Publication
    Steigerung der Energieeffizienz mittels Energiekennzahlen am Beispiel der Metallverarbeitung
    ( 2022)
    Sigg, Stefan
    ;
    Kühn, Armin
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    Schmidt, Alexander
    ;
    Roder, Sven
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    Thiele, Gregor
    ;
    Krüger, Jörg
    Die Energiewende und die einhergehende Forderung nach Effizienzsteigerungen stellen produzierende Unternehmen vor betriebliche und technische Herausforderungen. Methoden und Technologien des Energiemanagements gewinnen damit auch im Mittelstand an Relevanz. Dabei sind Kennzahlen ein Schlüssel, um die aktuelle Energieeffizienz einzuschätzen und Potenziale für Einsparungen zu identifizieren. Der Artikel dokumentiert Erfahrungen der Anwender mit Bezug auf Konzepte aus der Wissenschaft, um Interessierten aus der Industrie den Einstieg in das Thema zu erleichtern.
  • Publication
    Decomposition of a Cooling Plant for Energy Efficiency Optimization Using OptTopo
    ( 2022)
    Thiele, Gregor
    ;
    Johanni, Theresa
    ;
    Sommer, David
    ;
    Krüger, Jörg
    The operation of industrial supply technology is a broad field for optimization. Industrial cooling plants are often (a) composed of several components, (b) linked using network technology, (c) physically interconnected, and (d) complex regarding the effect of set-points and operating points in every entity. This leads to the possibility of overall optimization. An example containing a cooling tower, water circulations, and chillers entails a non-linear optimization problem with five dimensions. The decomposition of such a system allows the modeling of separate subsystems which can be structured according to the physical topology. An established method for energy performance indicators (EnPI) helps to formulate an optimization problem in a coherent way. The novel optimization algorithm OptTopo strives for efficient set-points by traversing a graph representation of the overall system. The advantages are (a) the ability to combine models of several types (e.g., neural networks and polynomials) and (b) an constant runtime independent from the number of operation points requested because new optimization needs just to be performed in case of plant model changes. An experimental implementation of the algorithm is validated using a simscape simulation. For a batch of five requests, OptTopo needs 61 (Formula presented.) while the solvers Cobyla, SDPEN, and COUENNE need 0.3 min, 1.4 min, and 3.1 min, respectively. OptTopo achieves an efficiency improvement similar to that of established solvers. This paper demonstrates the general feasibility of the concept and fortifies further improvements to reduce computing time.
  • Publication
    Towards High-Payload Admittance Control for Manual Guidance with Environmental Contact
    ( 2022)
    Haninger, Kevin
    ;
    Radke, Marcel
    ;
    Vick, Axel
    ;
    Krüger, Jörg
    Force control enables hands-on teaching and physical collaboration, with the potential to improve ergonomics and flexibility of automation. Established methods for the design of compliance, impedance control, and collision response can achieve free-space stability and acceptable peak contact force on lightweight, lower payload robots. Scaling collaboration to higher payloads can allow new applications, but introduces challenges due to the more significant payload dynamics and the use of higher-payload industrial robots. To achieve high-payload manual guidance with contact, this paper proposes and validates new mechatronic design methods: standard admittance control is extended with damping feedback, compliant structures are integrated to the environment, and a contact response method which allows continuous admittance control is proposed. These methods are compared with respect to free-space stability, contact stability, and peak contact force. The resulting methods are then applied to realize two contact-rich tasks on a 16 kg payload (peg in hole and slot assembly) and free-space co-manipulation of a 50 kg payload.
  • 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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    Kohl, Holger
    ;
    Krüger, Jörg
    ;
    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
    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.
  • Publication
    Augmented learning for industrial education
    ( 2020)
    Menn, Jan Philipp
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    Severengiz, Mustafa
    ;
    Lorenz, Andrea Katherija
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    Wassermann, Jonas
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    Ulbrich, Carsten
    ;
    Krüger, Jörg
    ;
    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
    ( 2020)
    Lehr, Jan
    ;
    Schlüter, Marian
    ;
    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.