Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK

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  • Publication
    Development of an Industrial Internet of Things Ontologies System
    ( 2020)
    Fedotova, Alena V.
    ;
    Lindow, Kai
    ;
    Norbach, Alexander
    The work is aimed at researching and developing an innovative subject field Industrial Internet of Things. The article deals with the system of the structure of the Industrial Internet of Things, the relationship between the objects of structure and the method of knowledge visualization with the help of ontological modeling of systems. Using the ontological approach allows us to provide support for design management, as well as further improvement of the complex technical system under consideration. The paper presents the ontology of the Industrial Internet of Things.
  • Publication
    Applying Contextualization for Data-Driven Transformation in Manufacturing
    ( 2020)
    Gogineni, Sonika
    ;
    Lindow, Kai
    ;
    Nickel, Jonas
    ;
    Stark, Rainer
    Manufacturing is highly distributed and involves a multitude of heterogeneous information sources. In addition, Production systems are increasingly interconnected, hence leading to an increase in heterogeneous data sources. At present, data available from these new type of systems are growing faster than the ability to productively integrate them into engineering and production value chains of companies. Known applications such as predictive maintenance and manufacturing equipment management are currently being continuously optimized. While these applications are designed to help companies manage their manufacturing and engineering data, they only use a fraction of the total potential that can be realized by linking manufacturing and engineering data with other enterprise data. In the future, the context in which the data can be set will play an essential role. A meaningful added value in manufacturing can be achieved only with context specific data. Against this background, this paper presents three main areas of application for contextualizing data (semantics, sensitivity and visualization) and explains these applications with the help of a contextualization architecture. The concept is also evaluated using an industrial example. Furthermore, the paper describes the theoretical background of contextualization and its application in industry. The major challenges of the ability of engineers to adapt their activities and the integration of process knowledge for semantic linking are addressed as well.
  • Publication
    Use of Digital Twins in Additive Manufacturing Development and Production
    ( 2019)
    Bergmann, André
    ;
    Lindow, Kai
    The megatrend of the digitization of the industry is picking up speed. Today, the digital twin is an important component in the strategic positioning of a manufacturing company. The Gartner Report predicts that more than 50% of large industrial companies will be using the digital twin and that the effectiveness of the companies can be increased by up to 10% by 2021. For this, it is necessary on the one hand that the products are equipped with sensors, in order to be able to provide the data for the digital twin. On the other hand, it is also necessary to be capable to evaluate the data unambiguously with regard to the products and to be able to initiate appropriate measures to control them. In addition, insights can be gained into the improvement of subsequent product generations and their production. The virtual representation of the product over its lifecycle requires a coupling with the real environment, in which lifecycle data are recorded via sensory systems and continuously imported into the virtual environment. Thus, the information and actual properties in the digital twin are mapped to the real conditions and the product condition in a dynamic data model. For this, it is necessary to integrate the information into the data systems of the product development and manufacturing processes. Based on this data, the behavior can be virtually tested, analyzed and predicted before actual production and use. This enables the engineer and manufacturer to further develop the product at reduced costs as early as the design phase. The virtual validation is significantly extended by the collected database in the digital twin. For companies, this means a reduction of costs by reducing material and time expenditures as well as process times - for example, with increased utilization time. On the basis of this study, a product example will be used to show which framework conditions are necessary for the use of the digital twin and which effects can be achieved in product development. It is also estimated to what extent the quality of the product and the process can be improved. In the area of additive manufacturing, for example, the question arises how quality data can be used either to control the machine parameters of the printing process in a targeted manner (feedback-to-planning) so that the desired product quality is achieved, or to adapt the product models before manufacturing (feedback-to-engineering) so that the desired product quality can be produced with existing parameters. The data alone is of little use to the companies. In addition to methodological and organizational issues, it is also necessary at the technological level to prepare the data for the various lifecycle phases of the product development process. This is where automated data evaluation in the form of AI comes in. Algorithms allow data evaluation by identifying patterns and deviations and consequently interpreting them for feedback-to-planning and feedback-to-engineering.
  • Publication
    Feedback to Design with Digital Lifecycle-Twins - literature review and concept presentation
    ( 2018)
    Riedelsheimer, Theresa
    ;
    Lindow, Kai
    ;
    Stark, Rainer
    In this paper, the authors propose a concept for optimizing the design process as well as product-related features and services through learning from Digital Twin data and establishing a continuous feedback loop from downstream phases of the product lifecycle to the design phase. As a first step, a systematic review of existing concepts in literature as well as a gap analysis is conducted. The presented concept details existing Digital Twin concepts and implementations by focusing on the specific objective of realizing Feedback to Design and integrating the lifecycle aspect.