Modeling IT Availability Risks in Smart Factories. A Stochastic Petri Nets Approach
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.