Cube, Johann Philipp vonJohann Philipp vonCubeHärtel, LasseLasseHärtelSchmitt, RobertRobertSchmittPonsard, ChristopheChristophePonsardMassonet, PhilippePhilippeMassonetLandtsheer, Renaud deRenaud deLandtsheerOspina, GustavoGustavoOspinaPrintz, StephanStephanPrintzJeschke, SabinaSabinaJeschke2022-03-052022-03-052016https://publica.fraunhofer.de/handle/publica/24709710.1016/j.procir.2016.11.029Various approaches exist to quantify risks in supply chains. However, two aspects in risk assessments are not usually considered: monetarized risk quantification and use-case dependent model complexity. Monetarily quantifying risks means quantifying root-cause and severity of each single risk and aggregating these risks into an aggregated risk value. Thereby information uncertainty, complex interrelations and dynamic influences need to be considered. Depending on a use-cases goal information or process models need to be created at different levels of detail. This paper presents a Discrete Event Simulation (DES) approach providing all necessary features to monetarily quantify risks in dependent of the depth of information and thus allow adjusting the model dependent on the use-case. It provides graphical modeling language equipped with risk assessment probes enabling to capture all risk-relevant aspects. Based on this instrumented model, the framework is then able to compute and report about monetary risk quantification using an efficient DES engine driven by a Monte-Carlo procedure. Within this paper applicability of such an approach shall be assessed in use-case specific processes characterized by determined risks and parameter settings.enmonetary risk quantificationdiscrete event simulationMonte Carlo simulationuse-casesQM-MethodenRisikomanagementSimulationjournal article