13.2: Points Made in the Case Study

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The automatic inventory system in this case study illustrates a fundamental consideration of demand and inventory management: the cost of holding inventory trades off with the need to meet customer demands.

Entities sometimes do not represent physical entities. In this case, a entity represents control information flowing within the inventory system.

A system can respond to changes in state variable values. The inventory system responds to changes in the amount of inventory on hand. When critical values are reached, state events, in the form of arriving entities, occur and initiate appropriate responses. The ability to model the dynamic response of a system to state variable values changes is a unique simulation capability.

A Monte Carlo simulation is usually defined as taking samples of one or more random variables, manipulating the samples, and gleaning information from the results in a situation where time plays no substantive role. This simulation experiment has these Monte Carlo characteristics. However, multiple points in time, each separated by one day, are considered. Changes in state variable values from day to day, determined by the random samples, are significant components of the simulation.

In previous case studies, detailed operations effecting individual entities are modeled. In this system, the aggregate affect of production and sales on inventory management are described. Statistical distributions are used to quantify this aggregate behavior. Manipulations of these distributions based on principles of probability and statistics assist in determining system and model parameter values.

The model used in this case study illustrates a simulation capability of fundamental importance. The model consists of three processes. Each process changes the values of the same state variables. The processes independently determine what actions to take based on the current state variable values. However, no information is explicitly transmitted between the processes. The simulation engine transparently performs all co-ordination tasks.