The data-driven simulation approach and the Supply Chain Model Builder software are basically tactical level tools. They can be further extended to integrate with strategic and operational level modeling and simulation work.

VIVACE WP2.1 includes an activity involving modelling of the future business environment for air transport, which is being addressed through scenario planning. The potential future business environment yielded by scenario planning may provide input to the WP 2.5 supply chain modelling and simulation work in a few ways:

• By identifying conceptual supply chains that it might be desired to explore (i.e. scenarios concerning which manufacturers are active within the supply chain)
• By proposing demand patterns as a result of scenarios (these would be inputs to the simulation model, for the purpose of assessing the performance of the simulated supply chain under a given set of circumstances). Long term demand scenarios from WP2.1 will be sliced to obtain short term stable demand scenarios for WP2.5 for each phase of the former.
• By addressing business interfaces between actors in the aerospace industry. If present-day interfaces are found to be poor – if communication delays exist between elements of the supply chain – these time lags could and should be included within the information flow sections of the supply chain model.

On the feedback loop, results from supply chain simulation work can be used to refine future business and demand scenarios.

These imply the requirement of long term (strategic) data exchange of supply chain infrastructures, demand scenarios, important supply chain control parameters and supply chain information flow.

Similarly, data-driven supply chain simulation can be integrated with company internal logistics and manufacturing workflow simulation, which is the work of VIVACE task 2.5.3 and also introduced on this website. 

Manufacturing workflow simulation focused on simulating the effects of different factory layout and logistics controls under detailed factory operational conditions. Unlike supply chain simulation work, detailed demand patterns, operator shifts, individual resource capacities and availabilities are used for manufacturing workflow simulation.

In its simplest form, integration between data-driven supply chain simulation and manufacturing workflow simulation can work in the following way:

Supply chain simulation exports weekly throughputs to manufacturing workflow simulation (to determine weekly factory outputs)
Manufacturing workflow simulation feeds the obtained throughput capacity back to supply chain simulation (to determine resource capacities)

Technically, these integrations can be implemented though common data types or the Collaboration Hub, which is being developed by VIVACE WP3.6. The concept of data-driven simulation is still relevant for these integrations as in the standalone supply chain simulation.