Supply chains face a myriad of adverse risks that impact their daily operations and make them vulnerable. Although several risk management methods exist, manufacturing companies - and especially supply chains - do not effectively utilize them. In addition, supply chains have difficulties in quantifying the effects of risks and creating appropriate mitigation strategies due to the lack of a structured approach. Therefore, we investigate means of simulating the goods flow in a manufacturing supply chain based on a real example of a supply chain in Sweden. This simulated data is used to explore and compare different artificial intelligence or statistics based forecasting models for future goods flow in a supply chain.