Now showing 1 - 2 of 2
  • Publication
    Modeling IT Availability Risks in Smart Factories. A Stochastic Petri Nets Approach
    ( 2020)
    Miehle, Daniel
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    Pfosser, Stefan
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    Übelhör, Jochen
    In the course of the ongoing digitalization of production, industrial production infrastructures have become increasingly intertwined with information and communication technology. There-by, physical production processes depend more and more on the flawless functioning of information networks. Threats, such as attacks and errors, can compromise the components of in-formation networks, and due to the increasing interconnection, can even cause entire smart factories to fail. However, increasing complexity and lack of transparency of information networks in smart factories complicate the detection and analysis of such threats. Following a De-sign Science Research approach, this study aims to develop a methodology to depict and to model information networks in smart factories to enable the identification and analysis of IT availability risks. Based on a modular stochastic Petri net approach, we provide an artifact that enables the simulation and analysis of threats in smart factory information networks. To demonstrate the applicability and feasibility of our approach, we investigate different threat scenarios regarding their impacts on the operational capability of a close-to-reality information network setting. Further, to complement the evaluation from a practical perspective, we integrated the insights from two expert interviews with two global leading companies in the automation and packaging industry. The results indicate that the developed artifact offers a promising approach to better analyze and understand IT availability risks in smart factory information networks.
  • Publication
    Development of dynamic key figures for the identification of critical components in smart factory information networks
    ( 2017) ;
    Miehle, Daniel
    ;
    Pfosser, Stefan
    ;
    Übelhör, Jochen
    Informational risks in smart factories arise from the growing interconnection of its components, the increasing importance of real-time accessibility and exchange of information, and highly dynamic and complex information networks. Thereby, physical production more and more depends on functioning information networks due to increasing informational dependencies. Accordingly, the operational capability of smart factories and their ability to create economic value heavily depend on its information network. Thus, information networks of smart factories have to be evaluated regarding informational risks as a first prerequisite for subsequent steps regarding the management of a smart factory. In this paper, we focus on the identification of critical components in information networks based on key figures that quantitatively depict the availability of the information network. To enable analyses regarding dynamic effects, the developed key figures cover dynamic propagation and recovery effects. To demonstrate their applicability, we investigate two possible threat scenarios in an exemplary information net-work. Further, we integrated the insights of two expert interviews of two global companies in the automation and packaging industry. The results indicate that the developed key figures offer a promising approach to better analyse and understand informational risks in smart factory information networks.