Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK

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  • Publication
    A Process Model for Enhancing Digital Assistance in Knowledge-Based Maintenance
    ( 2019)
    Kovacs, Klaudia
    ;
    Ansari, Fazel
    ;
    Geisert, Claudio
    ;
    Uhlmann, E.
    ;
    Glawar, Robert
    ;
    Sihn, Wilfried
    Digital transformation and evolution of integrated computational and visualisation technologies lead to new opportunities for reinforcing knowledge-based maintenance through collection, processing and provision of actionable information and recommendations for maintenance operators. Providing actionable information regarding both corrective and preventive maintenance activities at the right time may lead to reduce human failure and improve overall efficiency within maintenance processes. Selecting appropriate digital assistance systems (DAS), however, highly depends on hardware and IT infrastructure, software and interfaces as well as information provision methods such as visualization. The selection procedures can be challenging due to the wide range of services and products available on the market. In particular, underlying machine learning algorithms deployed by each product could provide certain level of intelligence and ultimately could transform diagnostic maintenance capabilities into predictive and prescriptive maintenance. This paper proposes a process-based model to facilitate the selection of suitable DAS for supporting maintenance operations in manufacturing industries. This solution is employed for a structured requirement elicitation from various application domains and ultimately mapping the requirements to existing digital assistance solutions. Using the proposed approach, a (combination of) digital assistance system is selected and linked to maintenance activities. For this purpose, we gain benefit from an in-house process modeling tool utilized for identifying and relating sequence of maintenance activities. Finally, we collect feedback through employing the selected digital assistance system to improve the quality of recommendations and to identify the strengths and weaknesses of each system in association to practical use-cases from TU Wien Pilot-Factory Industry 4.0.
  • Publication
    NC-form grinding of carbon fibre reinforced silicon carbide composite
    ( 2013)
    Uhlmann, E.
    ;
    Borsoi Klein, T.
    ;
    Schweitzer, L.
    ;
    Neubrand, A.
    This paper presents an approach for the development and optimization of the NC-form grinding technology for an efficient machining of carbon fibre reinforced silicon carbide composite (C/SiC). The C/SiC properties, the importance and the necessity of the application of a high performance grinding process for the machining of this innovative composite material are introduced first. Then, the methodologies and the experimental investigations of NC-form grinding with the application of several machining parameters and three distinct bond types (vitrified, metal and synthetic resin) of diamond mounted points for the abrasive machining of C/SiC are presented. In order to monitor and analyze the process, grinding forces, surface integrity of ground workpieces and grinding wheel wear are investigated. The results of this paper provide new information regarding the wear behavior of grinding tools and the optimized conditions for grinding of C/SiC.
  • Publication
    Innovative Lösungen für Instandhaltung und Reparatur in Energie und Verkehr - ein Erfahrungsbericht aus dem Innovationscluster MRO (Maintenance, Repair and Overhaul)
    ( 2011)
    Uhlmann, E.
    ;
    Röhner, M.
    Im Mittelpunkt der diesjährigen Konferenz steht das Thema Trennen-Fügen-Oberflächenbeschichten (TFO) verbunden mit der Präsentation von Leitprojekten der Netzwerkarbeit unter anderem durch Kjellberg Finsterwalde, ArcelorMittal Eisenhüttenstadt, BTU Cottbus, Fraunhofer Institut für Produktionsanlagen und Konstruktionstechnik Berlin, Kompetenzzentrum TFO/EEpL Finsterwalde.
  • Publication
    Bauteile aus Pulver und Licht
    ( 2010)
    Urban, K.
    ;
    Uhlmann, E.