WIT Press

Simulation-based Risk Analysis In Production Networks


Free (open access)








730 kb

Paper DOI



WIT Press


C. Hans & J. Schumacher


Customer-driven markets, decreasing product life cycles and the demand for innovative custom tailored products are the main reasons for the evolution from single enterprises with a high vertical range of manufacture towards production networks. By utilising the basic experience of each of the involved partners such networks allow the fabrication of products in an individual, efficient and cheap way and therefore increase the competitiveness of the involved enterprises. Due to the multitude of different entities and their complex interrelations, risk is an omnipresent factor and has to be carefully considered for the planning and operation of production networks which have to be efficient and robust at the same time. In this context robustness means the resistance of networks against unexpected events like suddenly decreasing customer demands, accidents during transportation, breakdown of production or warehousing facilities, natural disasters or wars which can dramatically decrease their overall performance. Thus in addition to efficiency in terms of costs, lead times, etc. the robustness has become a crucial aspect for the configuration of high-performance production networks. The article describes the application of a simulation environment which is part of the ONE toolset [1] supporting the planning of efficient and robust enterprise networks. Based on the underlying ONE Network Model relevant risk factors related to processes (transportation, production, ordering, etc.) or parts of the network topology (natural disasters, wars, strikes, etc.) can be specified, simulated and analysed. In addition to a basic model assessment, the insights regarding the dynamic model behaviour which can be extracted from the simulation are also used to find better solutions and appropriate model adaptations. Keywords: risk analysis, simulation, risk modelling, production networks.


risk analysis, simulation, risk modelling, production networks.