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M.Sc. Philipp Gönnheimer

Akad. Mitarbeiter
Bereich: Maschinen, Anlagen und Prozessautomatisierung
Sprechstunden: nach Vereinbarung
Raum: Raum 015, Geb. 50.36
Tel.: +49 1523 9502578
Philipp GoennheimerDhy2∂kit edu

76131 Karlsruhe
Kaiserstraße 12


M.Sc. Philipp Gönnheimer

Forschungs- und Arbeitsgebiete:

  • Digitale Zwillinge und Informationsmodelle von Maschinen und Anlagen
  • Baukastenkonzepte für Produktionsanlagen
  • Themenbereich Industrie 4.0

 

Allgemeine Aufgaben:

 

Projekte:

  • I4TP - Deutsch-Chinesische Industrie 4.0 Fabrikautomatisierungsplattform
  • ROBOTOP - Modulare, offene und internetbasierte Plattform für Roboter-Anwendungen in Industrie und Service

 

Lebenslauf:

seit 01/2018 Wissenschaftlicher Mitarbeiter am Institut für Produktionstechnik (wbk) des Karlsruher Instituts für Technologie (KIT) 

Veröffentlichungen

[ 1 ] Barton, D.; Gönnheimer, P.; Qu, C. & Fleischer, J. (2018), „Self-describing connected components for live information access within production systems“. 4th International Conference on System-Integrated Intelligence: Intelligent, Flexible and Connected Systems in Products and Production, Hrsg. Denkena, B.; Thoben, K. & Trächtler, A., S. 250-257.
Abstract:
Access to data from components in production systems is potentially an enabler for various data-based approaches. This paper presents a practical approach to transform mechanical components into self-describing cyber-physical systems connected within a local network. The requirements for typical use cases are analysed and a modular cyber-physical connector is proposed. The data is collected by a central OPC UA client and fed into a web-based visualisation, so that it is easily accessible for operators, maintenance staff, and other stakeholders. The approach is illustrated for components with two different levels of complexity.

[ 2 ] Gönnheimer, P.; Kimmig, A.; Mandel, C.; Stürmlinger, T.; Yang, S.; Schade, F.; Ehrmann, C.; Klee, B.; Behrendt, M.; Schlechtendahl, J.; Fischer, M.; Trautmann, K.; Fleischer, J.; Lanza, G.; Ovtcharova, J.; Becker, J. & Albers, A. (2019), „Methodical approach for the development of a platform for the configuration and operation of turnkey production systems“. Procedia CIRP, Hrsg. Putnik, G., S. 880-885.
Abstract:
Shorter product lifecycles lead not only to faster time-to-market for products but also to the need for just as fast available associated production systems. These shorter product lifecycles, as well as the increasing individualization of products, also result in further decreasing production lot sizes. Young companies in China in particular are characterized by a very high speed of innovation but may not have the necessary manufacturing knowledge or capacities to bring their developed products to the market with a scalable production. For this reason, there is a great need to quickly set up and commission turnkey production systems or to reconfigure existing production systems for new production tasks in the shortest possible time. This paper describes the design and architecture of a cloud platform with the aim to support a manufacturer independent design process for turnkey production systems. This process ranges from the product to be manufactured to the operation of the production system. Firstly, the structure and methodology used to link the various objectives are discussed. The system for recording and structuring product and production system data to create reusable modules from components and machines is described. Subsequently, the use of standardized modules is developed to support reconfiguration of the production system during operation. In addition, the digital business models tailored to the production system are proposed to the platform user for commissioning and operation of the plant. A case study is conducted to validate the proposed methodology.

[ 3 ] Barton, D.; Gönnheimer, P.; Schade, F.; Ehrmann, C.; Becker, J. & Fleischer, J. (2019), „Modular smart controller for Industry 4.0 functions in machine tools“. Procedia CIRP, Hrsg. Butala, P.; Govekar, E. & Vrabič, R., S. 1331-1336.
Abstract:
In machine tools, Industry 4.0 functions can increase availability through predictive maintenance, while other functions improve productivity and workpiece quality through process supervision and optimisation. Many of these functions rely on data communication between systems from different suppliers. Requirements regarding latency and computing vary widely depending on the application. Based on an analysis of these requirements, a smart controller for the implementation of Industry 4.0 is designed, using a hypervisor to allow for the integration of soft real-time and best-effort applications.