Office of Quality Management Computer simulation modeling is a discipline gaining popularity in both government and industry.Designers, program managers, analysts, and engineersuse computer simulation modeling tounderstand and evaluate ‘what if’ case scenarios. Computer simulation modeling can assist in the design, creation, and evaluation of complex systems by replicating a real or proposed system using computer software when changes to the actual system are difficult to implement, involve high costs, or are impractical.Some examples of computer simulation modeling familiar to most of us include: weather forecasting, flight simulators used for training pilots, and car crash modeling. For more videos of OQM Computer Modeling and Simulation Projects,visit OQM andComputer Modeling and Simulation Projects(NIH-only access) Gain greater understanding of a process Identify problem areas or bottlenecks in processes Evaluate effect of systems or process changes such as demand, resources, supply, and constraints Identify actions needed upstream or downstream relative to a given operation, organization, or activity to either improve or mitigate processes or events Evaluate impact of changes in policy prior to implementation Discrete Models – Changes to the system occur at specific times Division of Property Management trouble calls Acquisition or construction business processes Amanufacturing system with parts entering and leaving at specific times Continuous Models – The state of the system changes continuously over time Areservoir as water flows in and out Chilled water or steam distribution Mixed Models – Contains both discrete and continuous elements Arefinery with continuously changing pressure inside vessels and discreetly occurring shutdowns Chilled water distribution including plant shutdowns The overall process flow and its associated resources What is being produced, served, or acted upon by the process (entities) Frequency at which the entities arrive in the process How long do individual steps in the process take Probability distributions that characterize real life uncertainties and variations in the process Shooter scenarios Shuttles Gateway Visitor Center OQM
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Types of Data/Information Needed to Develop a Simulation Model:
Examples of use in ORS/ORF include:
See Also
Model Limitations