Abstract
Due to globalisation, supply chains face an increasing number of risks that impact the procurement process. Even though there are tools that help companies address these risks, most companies, even larger ones, still have problems for adequately quantifying the risks on their current process as well as on alternative process. The aim of our work is to provide companies with a software supported method for quantifying procurement risks and establishing adequate strategies for risk mitigation at an optimal cost. Based on the results of a survey on risk management practices and industrial needs, we developed a tool that enables them quantifying these risks. The tool makes it easier to express key risks via a process model that offers an adequate granularity for expressing them. A simulator incorporated in our tool can efficiently evaluate these risks through Monte-Carlo simulation technique. Our main technical contribution lies in the development of an efficient Discrete Event Simulation (DES) engine, together with a Query Language that can be used to measure business risks from the simulation results. We show the expressiveness and performance of our approach by benchmarking it on a set of cases that are taken from industry and cover a large set of risk categories.
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Acknowledgement
This research was conducted under the SimQRi research project (ERA-NET CORNET, Grant No. 1318172). The CORNET promotion plan of the Research Community for Management Cybernetics e.V. (IfU) has been funded by the German Federation of Industrial Research Associations (AiF), based on an enactment of the German Bundestag.
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De Landtsheer, R. et al. (2017). Assessment of Risks in Manufacturing Using Discrete-Event Simulation. In: Vitoriano, B., Parlier, G. (eds) Operations Research and Enterprise Systems. ICORES 2016. Communications in Computer and Information Science, vol 695. Springer, Cham. https://doi.org/10.1007/978-3-319-53982-9_12
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DOI: https://doi.org/10.1007/978-3-319-53982-9_12
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