Monte Carlo Simulation Modeling for Risk, Optimization and Forecasting Analysis

Learn probabilistic event and risk analysis using simulation

Course overview - 2 days

Monte Carlo Simulation Modeling for Risk, Optimization and Forecasting Analysis focuses on the principles of probabilistic event and risk analysis using simulation techniques, with an emphasis on using ReliaSoft RENO software to graphically build simulations utilizing flowcharts. This course also explores advanced risk and reliability analysis methods through integration with analyses, RBDs and/or fault trees created in BlockSim.

You will use ReliaSoft RENO along with other ReliaSoft platform software with hands-on practice and case study analysis.
Learning objectives
  • Define a problem, conceptualize how to obtain a solution via simulation, implement the flowchart in RENO, validate the model and use plots and other metrics to analyze and visualize the simulation results
  • Perform sensitivity analysis to evaluate how key inputs will affect the results
  • Automatically estimate optimum values by performing multiple simulation runs

Topics included:

  • Understanding deterministic vs. probabilistic analysis
  • Introduction to simulation
  • Introduction to building simulation models in RENO
  • Basics of risk decision analysis
  • Application of quantitative decision and risk analysis
  • Probabilistic design concepts
  • Advanced reliability simulation analysis applications
  • Maintenance application
  • Life cycle cost analysis and other financial applications

Who should attend?

This course is for design and maintenance professionals that desire to learn how to apply simulation techniques with reliability modeling and analysis that will enable the organization to study options and assess risk prior to expending time and financial resources in development and maintenance improvements.