Designing any machine can be a very expensive undertaking. One of the biggest advantages to utilizing simulation models as opposed to actual finished equipment, is cost effectiveness. Substantial cost savings can be had by using simulation models in the design, testing and redesigning phases in machine development. Developers can also use simulation models in ways that may not be possible to do with an the real machine. For example, intricate parts of some equipment might be damaged in the testing process. With a simulation model, developers can be more free to test all of the aspects of the machine, without worrying so much about damaging an expensive machine.
Simulation models can provide a high level of detail in experimental activities. Simulations can provide results that are generally not measurable in some experiments, within certain technology levels. The simulation exercises could also be set to operate for many more steps desired at multiple levels, and use a higher degree of intricacy. These circumstances can be more effective, given that the only restriction would be a user or developer's programming skill, specific device capability or their imagination.
The simulation model errors can pose a threat in the development or use of a machine, and incorrect key strokes can alter results. Without adequate results, a project can be delayed or fail. Because developers program using theories on how machines or software works, simulation model results may not be completely correct. Experimental results from simulation models must be verified to be accepted within the general community. Once the two data sets compare well, other simulation designs may have more credibility.
Because a simulation model is based on experimentation, one disadvantage is that it is not the actual machine that it replicates. This can pose a situation wherein the user and other people do not take it seriously from an engineering perspective. This is because they are not able to actually see, feel and hear the project as it would be in reality. Some engineers, for example, might be unwilling to invest the time it takes to develop a machine into using a simulation model. Also it can be difficult to read the results of a simulation model test, which would make it less successful for development purposes.