Simulation of a manufacturing facility requires modeling and recreation of the behavior and performance of each individual process and system.
In establishing the model, it makes sense to breakdown each process into its discrete parts. This makes it easier to analyze and allows more factors to be considered within the model.
Discrete Event Simulation (DES) software approximates continuous processes into defined, non-continuous events.
For example, Discrete Event Simulation software in a vehicle manufacturing facility would model the movement of a car part from Assembly into the Paint Shop as two events i.e. the departure event and the arrival event. The actual movement of the component would be represented only by the time lapse between the two events.
The entire manufacturing facility can be modeled as a sequence of operations being performed on passive entities, e.g. components, as they pass through the processing sequences. Although the components are passive, they have attributes that affect the way they are handled and some of these attributes change as the component advances through the processes.
In an Industry 4.0 application, IT innovations such as Big Data and Cloud Operation make real time data available for Discrete Event Simulation. The dynamic processes in a Smart factory enable operational flexibility that can respond to last-minute scheduling changes, hence Discrete Event Simulation software assists in planning to save time, reduce costs and minimize risk in the overall operation.
When the real system can't be run over and over with different configurations and settings, Discrete Event Simulation software proves easier than mathematical modeling and provides more realistic results. It effectively 'concertinas' time, allowing simulation of operations that may take days to run to be compressed into just a few seconds. Further, the simulation model can be easily adjusted when the effects of scaling up or down need to be studied.
The resulting information answers fundamental questions about the processes and overall system, for example how long a process takes, how frequently some equipment is used, how often rejects appear, etc. Consequently, it provides data on vital issues such as latency, utilization and bottlenecks for direct improvement in an Industry 4.0 setting.
In this way, Discrete Event Simulation assists with:
Although time consuming, the modeling stage requires the involvement of operators and personnel who are intimately familiar with the processes. This imparts an immediate sense of user involvement and ownership that can help in the later stage when implementing findings.
To that end, a realistic simulation also proves to be a much easier and faster tool for testing and understanding performance improvements in the context of the overall system, especially when demonstrating end results to users and decision makers.
In summary, Discrete Event Simulation software can provide competitive advantage when an Industry 4.0 installation needs to be optimized and controlled to manufacture the highest quality products in the shortest time to meet demand and maintain profit margin.