The tasks of planning and scheduiing in manufacturing have evolved from simplistic Material Requirements Planning systems to today's sophisticated Advanced Planning and Scheduling systems. While planning is concerned with the long-range determination of what needs to be manufactured, typically over a relatively long time period, scheduling is the task of deciding how that manufachlring is to be accomplished, typically over a relatively short time period. Simulation is well suited to the scheduling task since it can handle as much detail as is necessary to capture the subtleties of the manufacturing process. It is desirable for a simulation-based scheduling function to be integrated with an Enterprise Resource Planning system, which maintains the system data suitable for driving a simulation of the current system load and thereby producing a feasible schedule. This paper describes such an integrated system and the role of simulation within it.
SAINT is a modeling and simulation technique that provides the concepts necessary to model systems that contain tasks (discrete elements), state variables (continuous elements), and interactions between them.SAINT has been designed to facilitate the modeling and analysis of complex man-machine systems.This paper describes a SAINT network model of a real-time simulation of a drone control facility (DCF) in which operators monitor and control the flight of simulated remotely piloted vehicles (RPVs) through the use of visual (CRT) displays.
SAINT CONCEPTS AND THE RPV/DCF MODELThe SAINT (Systems Analysis of Integrated Networks of Tasks) simulation philosophy is to separate modeling from analysis. A graphical-network approach to modeling is taken, whereby a SAINT user describes the system to be analyzed through a network model and auxiliary descriptions. A SAINT network model contains a generalized set of symbols that facilitate the description of a system in network terms. The SAINT computer simulation program accepts a description of the model to be simulated and automatically performs an analysis to obtain estimates of statistical quantities that represent system performance. (Pritsker, 1974;.A SAINT model contains two basic components. The task-oriented component of the model is a network consisting of nodes, branches, and operators. The state variable component consists of the description of system variables that change values continuously over time.
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