With ever-increasing complexity, risk and dynamics of supply chains in manufacturing, simulation has become a powerful tool to assess supply chain performance. In conventional simulation approaches, the model is constructed by an expert user, who defines a model step-by-step via the interface of the simulation tool. Whenever the model configuration needs to be changed, this must again be carried out by a simulation expert, thus greatly limiting the usefulness of simulation to non-expert users.

Innovation. To resolve this, the concept of data-driven modelling/simulation has been explored in VIVACE WP2.5. In a data-driven simulation, the model is constructed automatically by a software program, based on data existing in company IT systems. Models created this way can be reconfigured rapidly, by changing the input data. Hence, a user could explore the implications of radical changes to a simulated supply chain or extended enterprise, despite having little knowledge of the simulation software itself. A prototype data-driven supply chain/extended enterprise modeller and simulation builder (SCMB) has been developed at the University of Nottingham (UNott). This was written in Visual Basic and includes codes to generate a supply chain data model and an Arena simulation model.

The SCMB has been verified, validated with and experimented on use case studies from Volvo Aero and Rolls Royce. These are based on the defined performance metrics that are shared with internal logistics simulation. Results show that the SCMB can be a useful tool in examining supply chain configurations and in predicting supply chain performance.

The following diagrams demonstrate the data-driven supply chain simulation process.