| Abstract Scope |
In principle, simulation is the imitation of a system based on knowledge and/or assumptions about the behavior of the various parts of that system. The goal is to develop insight into the whole system - including future behavior when changes are considered. In discrete-event simulation, the operation of a system is represented as a chronological sequence of events. One of the strengths is the ability to model stochastic (i.e. random) processes. This is accomplished by collecting data pertaining to the random behavior of each sub-component of the process. This data includes equipment failure rates, maintenance repair time, motion speed (or cycle rates) of equipment or individual processes, manual interventions to the processes and other factors such as working and non-working shift schedules, and the effects of upstream or downstream processes. This presentation outlines the practical use of data collection and simulation to aid the design and debottlenecking of Rodding Plants. |