# Increasing Resilience of Production Systems by Integrated Design
## 2 Materials and Methods
### Concurrent Supply Chain and Production Planning  
In order to investigate disturbances on production systems and the accompanying supply chain networks, material flow simulation provides appropriate options to study system behavior. According to Guideline 3633, Sheet 1 of the Society of German Engineers (VDI) [16], simulation involves the recreation of a system with dynamic processes allowing the investigation with experiments to generate findings that can, in turn, be transferred to the real system. Thus, it becomes possible to investigate the temporal behavior of the respective modeled system and to derive corresponding statements. For the investigation of processes, discrete-event flow simulations are often used, in which the time-related behavior of the system is represented by successive events of a processing list and the associated state changes.  
In an exemplary use case, a model was implemented in a Tecnomatix(r) Plant Simulation, which contains its own user interface to select production scenarios depending on the processing status of the implemented orders. A truck picks up the finished orders from the last day based on the first-in-first-out (FIFO) principle. Depending on the destination of the products, there is a separation between two different retrieval strategies. Inland locations allow partial deliveries, whereas abroad destinations require complete order fulfilment in one iteration. Disturbances can be turned on and off for the study of different scenarios with a simple button. This means that once the orders run through as planned (deterministically), there will be no delays in production. If the button is activated, disturbances with a defined mean time to repair (MTTR) are switched on, stochastic effects generate impacts on processes, and therefore, delays and unexpected events can occur.  
In its standard version, the modelled factory works in a 2-shift system. A total of two hours before end of production, a message is sent to the user to make a decision on how to proceed with further production. The user can base this decision on the status of the planned orders and the orders being processed at that time.  
In doing so, the user can select a scenario (e.g., start next shift) in the interface. This means that a third shift is run because the user assumes that the orders cannot be completely  
Figure 3: Reference Architectural Model Industry 4.0 [15].  
processed until the end of the second shift. In general, the user has three options as coping strategies for disturbance-related delays:  
* Option 1: Start third shift (as described above);
* Option 2: Increase production speed by a certain percentage. The default value in this case is 15%. Hence, orders may be completed by 10 pm after all or will continue to be processed the next day;
* Option 3: Continue as planned; in this case, it could be the case that the orders become behind schedule and have to be processed within the next day.  
The implementation and operationalization of the described options in a short-cycled and complex production environment necessitates the sophisticated description and modeling of system elements and their corresponding production processes. Therefore, an appropriate modeling approach and the derived process generation functionalities are described in the subsequent section.