A discrete event simulation approach for quantifying risks in manufacturing processes

Nowadays supply chains have to face an increasing number of risks related to the globalisation, especially impacting the procurement processes. Even though tools are available to help companies address those risks, most companies, even larger ones, still have problems to adequately quantify those risks and assess to what extend an alternative could address them. The aim of our work is to provide companies with a software supported methodology to quantify such risks and elaborate adequate risk mitigation strategies at an optimal cost. Based on a survey conducted about the risk management practices and needs within companies, we developed a tool that enables a constant focus on risks by enabling the easy expression of key risks together with the process model and hence help to focus the granularity of the model at the right level. Based on the model, a simulator can then efficiently evaluate these risks thanks to well-known Monte-Carlo simulation techniques. Our main technical contribution lies in the development of an efficient discrete event simulation (DES) engine together with a query language which can be used to measure business risks based on simulation results. We demonstrate the expressiveness and performance of our approach by benchmarking it on a set of cases originating from the industry and covering a large set of risk categories.