Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK

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  • Publication
    Steigerung der Energieeffizienz mittels Energiekennzahlen am Beispiel der Metallverarbeitung
    ( 2022)
    Sigg, Stefan
    ;
    Kühn, Armin
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    Schmidt, Alexander
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    Roder, Sven
    ;
    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
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    Sommer, David
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    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
    A practical approach to reduce energy consumption in a serial production environment by shutting down subsystems of a machine tool
    ( 2019)
    Can, Alperen
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    Thiele, Gregor
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    Krüger, Jörg
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    Fisch, J.
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    Klemm, C.
    Energy efficiency in production is becoming increasingly important for the automotive industry, motivated by political regulations and competitiveness. Many theoretical approaches to achieve an efficient production via advanced control have only been tested in experimental environments. Important for the transfer into serial production is the proof that all requirements (e.g. quantity and quality) will be met. For ensuring production on demand, machine tools (MT) imitate the real production process to keep themselves at operating temperature. All subsystems of a MT operate at full power in this state, disregarding its necessity. Shutting down these subsystems during non-productive periods is a promising approach for saving energy. This paper will present a method for shutting down components during non-productive periods, while ensuring the ability to produce on demand. Successful tests were already performed during live operation in a plant of a car manufacturer in Berlin, Germany.