*Queueing system.*This is one of the most often used models. We will study queueing system in great detail later. Queueing system can have a lot of variations that can be used to model many real life situation. We have seen a few examples in earlier chapters.Queueing systems often include random variables such as service time at various server(s); inter-arrival time for various customer streams; routing distribution of customers.

Example 6.8, 6.9 on page 193. Emphasize on the case where empirical data can produce histogram which shows the trend, often close to a mathematical model.

*Inventory system.*This is another model used to simulation storage problems, inventory problems. A typical inventory has three random variables: the number of units demanded per order or per time period; the time between demands; the lead time.*Reliability and maintainability.*Time to failure of a component, of a system.*Limited data.*When complete data is not avaiable, three distributions can be used to model the system, uniform, triangular, and beta distribution.*Other distributions.*A few other distributions can be used to model systems that are not covered above: Bernoulli and binomial distributions are for discrete system; hyperexponential may be useful in other instances.