Simulation
We seek to understand
highly stochastic processes
Most processes are stochastic in reality, being better described through random variables.
When you want to evaluate stock levels at critical points, the sizing of fleets, the effect of demand peaks, the dispersion in the times of any process, the flow of materials in production systems or the design of new production lines, it is essential to use tools that consider the inherent uncertainty in each process.
Understanding the
process variability
If you have a design problem, a resource sizing problem or a production or service process where there is a great stochastic character, simulation approaches can provide you with great solutions.
Scenario evaluation and optimization
This type of methodologies allows the evaluation of multiple What-If scenarios, varying structures, designs, resources, times, among other variables to see the effect on key process indicators.
Impact on services
A service can also be modeled and simulated. Understanding the resources associated with each stage, the queues and logics involved, in order to maximize the level of service and minimize the resources affected.
Large volumes of data
Working with large volumes of data is key to be able to statistically represent each sub-process in a rigorous way.
How do we implement a simulation-based tool?
01
Depending on the problem addressed and the client's requirements, we create the data ingestion and preprocessing procedures, as well as the interfaces and dashboards required for the analysis of the results.
02
We develop the necessary software so that the decision making tools have high levels of usability and can be useful in daily decision making processes.
Software we work with
