Discrete Event Simulation (DES) is a form of simulation that considers a system as a discrete collection of events, with each event having some defined effect on the rest of the system. The individual processes that comprise a system can each be defined in terms of their system impact, resource requirements, and trigger (may be scheduled, random, or in response to another system event). Once these constituent parts have been defined, they can be combined within the model to recreate the system from the ground up.
An advantage of this approach is its speed and configurability. Unlike continuous simulation models, in which each time slice is considered equally, DES is able to accelerate results considerably by only considering events which alter the state of the system. Additionally, since the system is defined from the bottom up, changes to low level processes can be trialled virtually instantly, without having to reconfigure high level logic.
Below is a selection of DES projects completed by BMT. This shows a variety of contexts for DES and the outputs and insights that can be generated through the simulation process.
- Options analysis: Trial various infrastructure/personnel/resource changes without the need for costly physical trials.
- Throughput analysis: Generate utilization metrics to identify the bottlenecks within the system.
- Planning: Use model of proposed system to develop understanding of resource requirements and timeline.
- Optimisation: Optimise system performance against selected KPI’s
In practice, simulation can provide support across the asset lifecycle:
We adopt a consultative approach, commencing with stakeholder discussions in order to establish the relevant system requirements and behaviour. Key input data can then be collected and a preliminary model established. This is followed by an iterative process in which model logic and behaviour is validated by stakeholders. This approach allows clients to have confidence in the model being constructed, not only because results can be compared to real world data, but because they can view how individual activities are informing the larger picture. Once model validity has been agreed, it can be used to trial proposals and test assumptions, as well as investigate the relationship between various inputs and KPI’s.
For general enquiries relating to Discrete Event Simulation, please contact Aidan Depetro
BMT Design & Technology