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The impact of digitalization on the chemical process industry will lead to a decentralized, highly automated production environment, in which intelligent products supervise and control their own production processes. There has been little work directed to the impact of digitalization on chemical plants. Traditional risk management methods are problematic in this highly complex environment. One method suitable for complex systems is the functional resonance accident method FRAM. FRAM analyses examine performance variabilities of functions and the couplings between these functions. The aims of this study were to analyze and simulate the risk and performance variability of chemical plants in dependence of their digitalization maturity. As this study was also exploratory in its nature, an additional goal was the identification of future research topics. To accomplish this research agenda, a new hybrid simulation methodology, that combines functional resonance accident methodology and fuzzy logic to simulate chemical plants, was developed. This simulation methodology can generally be used to identify risks in complex socio-technological systems. A new metric was proposed and used to identify critical couplings. In this study three plants, representing three different digitalization maturity levels, were designed in a case study. The results of the FRAM methods supported the theory that digitalization leads to a general lower performance variability. If disturbances were introduced into the simulation, the results were inconclusive. Supplementing these findings, an FTA analysis for the specific top event run-away reaction showed the correlation between this top event and the digital maturity level of the chemical plant.