Simulation of a manufacturing system



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The purpose of this study is the development of a simulation model for analyzing the behavior of a manufacturing system. The system examined was a batch-production operation that manufactured several sizes of a product consisting of a number of parts. These parts were produced on separate machines, stored in a finished parts inventory, and assembled on a single final assembly line on customer demand. Randomness was introduced in customer demand, production lead time, and final assembly capacity in order to more realistically simulate the operation. Both final assembly capacity and production lead time were generated from normal distributions. Customer demand was generated from an empirical distribution, a truncated normal distribution, and Poisson distribution. Compared results indicate that variability of the empirical distribution was greater than that of either of the other two distributions. This fact resulted in a significantly lower system service level for the empirical demand frequency simulation. An iterative simulation procedure was developed to determine economical safety stocks. It was compared with an approximation method taken from the literature. The Iterative method was found to give better results.