Modeling a converting line using discrete event simulation - to evaluate the effects of different production strategies

Abstract: The purpose of this Master’s Thesis is to create a model of a converting line factory. The model will be used to investigate factory performance when altering the order structure as well as other what-if scenarios. The model should also be easily adaptable so that it can be used to model other factories as well without the need to rebuild it from scratch. The main results of this study show that the throughput of the system is very stable when it comes to changing the order structure. The orders can be shortened without too much losses of throughput, the real performance dip doesn’t occur until the orders have been shortened to less than 30%. The baseline scenario for the model has a throughput of 17.14 million meters per month. Doubling the order lengths gives a slight but still significant increase of the throughput by 1.4 million meters. Shortening the order length to 30% decreases the throughput by 0.8 million meters which might be an acceptable solution if the factory needs to run shorter orders. Further decreasing the order lengths causes a steeper decline of performance. At 20% order length the throughput is 14.55 million meters per month, and at 10% it decreases to 11.27. Another conclusion from the output of the model is that the current transportation system is adequate for the factory. Removing the travel times doesn’t significantly increase the throughput of the factory. Finally, experiments with FIFO-strategies (First In First Out) showed that the factory’s performance suffers when removing the sequencing of orders that currently is in use. Removing buffers between the machines as well creates a drastic drop in throughput.