By Dr. Steven Dam
Risk Analysis is a part of every decision we make. Uncertainty, ambiguity, and variability are in constant flux as we move along in projects and try to determine the risk in each scenario we encounter. This is the purpose of the Monte Carlo Simulator. In every simulation, whether Monte Carlo or Discrete Event, we need something to simulate.
The Monte Carlo simulator provides us with a statistical range of possible outcomes and the likelihood that they occur for any choice of actions in our diagrams. Innoslate Monte Carlo simulations use data within the entities and models to determine the likeliness of how things will transpire from your models.
Monte Carlo Simulation is a very powerful tool for Program and Project Managers, as well as Systems Engineers. Innoslate’s Monte Carlo simulation provides histograms that display duration values, time constraints, cost charts broken down by individual cost of resource or event, total simulation cost, resource acquisition, the breakdown of availability during the simulations, and cost constraints put on the budget by the resources.
Discrete event simulation is a simple concept that models the system as a discrete sequence of events. In this case, we are simulating one sequence of the model.
Discrete event simulation in Innoslate will provide a Gantt chart result to reflect the time, cost, and decisions made during the simulation. The output will also provide the resources used during the simulation and where the gaps are in resources used during the event
Whether you want to run a single sequence of events or a prediction simulation, Innoslate provides both methods of simulation. Monte Carlo was developed during WWII and has been in use ever since while Discrete Event shortly followed thereafter. Both are very powerful and helpful tools in the world of modeling and simulation. Innoslate provides both for the user, and the valuable data produced allows for better accuracy and tracking of assets during a project, while keeping costs low and efficiency high.