a-real-world-example-for-student-learning-btsu-cafeteria-simulation.pdf

Data were not recorded by our sme and thus we had to

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data were not recorded by our SME, and thus we had to rely on our personal observations to get the processing times for each station. Nevertheless, the SME provided some statistics for the popularity of each station by their respective names ordered from most popular to least popular. As mentioned earlier, we also added our own observation to make sure that the obtained model would be as close to real one by visiting to the Nest multiple times. The only concerns making the results slightly unreliable was the fact that not having info on the schedules shift of the personnel. After applying all numbers into the model and testing the base model several times for accuracy, we decided to perform additional testing by some case studies. In order to make the queueing times shorter, we decided on two solutions to test: adding an extra worker at more populated food stations (Panda Express, Steak Escape, and Chickendipity) to act as a food-runner, who is a person that makes sure there is no down-time when food starts to run out.
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The second solution was based on changing the popularity factor of each food station to spread it more evenly. The reason were based on observations on certain lines were most crowded during the peak hours of service and thus leading to longer queue times. If the customers were more evenly distributed to the less populated food stations, then the overall average queue times of customers should decrease. This solution would also make use of the idle time of workers from the least popular food stations. The popularity factor could be controlled by e.g. offering special deals at other food stations, adding new items to the menu of other food stations, etc. 4.3. Project Limitation and Strengths The project encountered several limitations, such as time, detailed statistics, implementation of logical human decisions, and the area of the cafeteria that the model represents. Time was a major limitation as it proved to be difficult to keep up with the project schedule due in 6 weeks. Detailed statistics became an issue since the head manager of the Falcon's Nest, was concerned that some released information might harm BGSU. Consequently, we limited the simulation scope to what we could deliver in 6- weeks’ time period. We succeed doing so by delivering a reliable simulation model with four scenarios: a base model, an improved model, an advanced one, and the final model. The next section will describe the details of the models. 5. Simulation Models Four phases were used to develop the needed models: base, intermediate, advanced, and final models. In the following subsection, the details of these models will be described. 5.1. Base Model The base model had very basic setup as shown in Figure 1. The objective was focused only to test one station where the costumers arrived to the station, to get their food, and then move to the checkout station with queues connecting each station. This model gave the needed start point and statistics to advance to the next model.
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  • Fall '08
  • LOOMBA,A
  • Computer simulation, NEST

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