Question

Help: Why is it difficult to verify a simulation model? What are the areas of application for simulation? What are the limitations of simulation models?

Answer 1

Verification is the process of determining that a model implementation and its associated data accurately represent the developer's conceptual description and specifications.Verification is an iterative process aimed at determining whether the product of each step in the development of the simulation model fulfills all the requirements levied on it by the previous step and is internally complete, consistent, and correct enough to support the next phase.Subsystem verification and validation do not guarantee system credibility. Each sub model may produce valid results and the integration of models can be verified to be correct, but the simulation can still produce invalid results. Most often this occurs when the subsystem conceptual design includes factors that are not considered in the system conceptual design, or vice versa.

Simulation provide users with practical feedback when designing real world systems. This allows the designer to determine the correctness and efficiency of a design before the system is actually constructed.Simulation is used in many contexts, such as simulation of technology for performance optimization, safety engineering, testing, training, education, and video games. Mining and construction. In the mining sector, simulators are used to train operators. Agriculture. Livestock management operates with a tight profit margin.Health care sector, Corporations etc.

Disadvantages of taking a simulation approach to solve a management problem are indicated below:

1. Simulation is not precise. It is not an optimization process and does not yield an answer but merely provides a set of the system’s responses to different operating conditions. In many cases this lack of precision is difficult to measure.
2. A good simulation model may be very expensive. Often it takes years to develop a usuable corporate planning model.
3. Not all situations can be evaluated using simulation. Only situations involving uncertainty are candidates, and without a random component, all simulated experiments would produce the same answer.