Summary form only given. In simple queueing models, the average processing rate is assumed to be constant - regardless of the number of entities in the queue. In many real systems, the effective processing rate often increases as the queue builds (by working faster or adding resources) and decreases as the queue empties (by working slower or shedding resources). Whether planned as part of the production control management, or unplanned as human nature, the effect is often causing the corresponding queueing systems to be more stable than predicted by simple queueing models. Discrete event simulation models can easily handle this complexity. This case study demonstrates the basics of variable rate processing, and illustrates its effective use in capacity simulation models at Mimeo.com.