Modeling and Analysis of a Manufacturing Plant Using Discrete Event Simulation

Abstract

Today"s manufacturing systems are characterized by large number of complexities such as random arrival patterns of jobs, random processing times, random failure rates, random repair times, random rejection of parts, etc. The analytical models cannot capture all the randomness mentioned above into the models. There is a need to incorporate them into models to have a practical and real life model. Simulation comes handy in this aspect. Discrete Event Simulation (DES) is used to model a manufacturing system to predict its performance. The inputs to this model include arrival rate, batch size, setup time, processing time, machine breakdown rate, machine breakdown frequency, machines and their capacities, buffers, rejection percentage and inspection time. The outputs that are estimated are work in process, flow time, utilization and throughput.