neoladating powered by vbulletin - Validating a process model

(See Figure 1.)Consider a modeler building a model to represent a queuing system at an ice cream stand.

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In this case, even though the model passed the verification process, it does not represent behavior of the real system and fails the validation process.

Why are both verification and validation of a model needed?

Basically, if it is desirable for the model to return a rounded-up integer value of = 4 is entered? Validation is the process to ensure that the model is representing the real world as much as possible.

The validation process helps a modeler be certain the correct model is built.

This leads to unrealistic prediction, misguided results and a loss of the integrity of the model.

Verification is the process that ensures that the model is producing or predicting the right outcomes based on the relationships of input variables and output variables that are built into the model.

After that, the team builds a model using simulation software.

Based on the data that was collected and statistically analyzed, the team found that the processing time of Machine A is normally distributed with a mean of 5 minutes and a standard deviation of 1 minute, Machine B has a constant processing time of 1.5 minutes and Machine C has a constant processing time of ten minutes.

Simulation models can be built using computer software. Box said, “Essentially, all models are wrong, but some are useful,” which reminds the practitioner that neither is a model the real-world process nor can that process be fully represented.

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