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If you want to observe the effect of the informational, organizational and environmental changes on the model’s behavior. 3. The knowledge gained during the designing of a simulation model could be a great value toward suggesting improvement in the system under investigation. 4. Discover the important variables in the system, and discover how they interact. 5. Simulation can be used to verify analytical Solutions. 6. Animation shows a system in simulated operation so that the plan can be visualized.
When Simulation is not appropriate?
Simulation should not be used when: 1. The problem can be solved by common sense or analytically. 2. It is easier to perform direct experiments 3. The costs exceed the savings 4. The resources or time are not available. 5. The system behavior is too complex or can’t be defined.
Summery
1. The simulation gives you the ability to explore new policies, operating procedures, or methods without the expense and disruption of experimenting with the real system. 2. By using simulation to perform bottleneck analysis, you can discover the cause of the delays in work-in-process, information, materials, or other …show more content…
It is necessary to consider those aspects of the system that affect the problem under investigation
Types of Models
Models can be classified as being mathematical or physical. A simulation model is a particular type of mathematical model of a system. Simulation Models may be further classified as being static or dynamic, deterministic or stochastic, and discrete or continuous. * physical Model: it has been found useful to build physical models to study engineering systems. * mathematical Model: representing a system in terms of logical and quantitative relationships that are then manipulated and changed to see how the model reacts, and thus how the system would react. * static simulation model: is a representation of a system at a particular time. * dynamic simulation model: represents a system as it evolves over time. * Deterministic simulation model: If a the simulation model does not contain any probabilistic (i.e., random) components, it is called deterministic * Stochastic simulation models: Having at least some random input components produce output that is itself random, and model therefore be treated as only an estimate of the true characteristics of the
When Simulation is not appropriate?
Simulation should not be used when: 1. The problem can be solved by common sense or analytically. 2. It is easier to perform direct experiments 3. The costs exceed the savings 4. The resources or time are not available. 5. The system behavior is too complex or can’t be defined.
Summery
1. The simulation gives you the ability to explore new policies, operating procedures, or methods without the expense and disruption of experimenting with the real system. 2. By using simulation to perform bottleneck analysis, you can discover the cause of the delays in work-in-process, information, materials, or other …show more content…
It is necessary to consider those aspects of the system that affect the problem under investigation
Types of Models
Models can be classified as being mathematical or physical. A simulation model is a particular type of mathematical model of a system. Simulation Models may be further classified as being static or dynamic, deterministic or stochastic, and discrete or continuous. * physical Model: it has been found useful to build physical models to study engineering systems. * mathematical Model: representing a system in terms of logical and quantitative relationships that are then manipulated and changed to see how the model reacts, and thus how the system would react. * static simulation model: is a representation of a system at a particular time. * dynamic simulation model: represents a system as it evolves over time. * Deterministic simulation model: If a the simulation model does not contain any probabilistic (i.e., random) components, it is called deterministic * Stochastic simulation models: Having at least some random input components produce output that is itself random, and model therefore be treated as only an estimate of the true characteristics of the