McCload
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Jewel Winkler
DSCI 6613
MW2:00-3:15
Executive Summary
I recommend that we decrease the average service times for all food stations as well as reduce the minimum service time for the interactive cooking station and increase the inter-arrival time. We can implement this by offering specials a half hour to an hour before the rush period begins, have enough precooked meals available to accommodate the rush and precook the ingredients for the interactive station. We can also have the manager step in as the second cashier whenever a certain amount of time transpires. The cashier on duty can signal to the manager by hand gestures or a light when the wait time has exceeded two minutes, respectively. I also recommend that the layout of the cafeteria be changed. The new layout will give us better organization of the lines in order to decrease confusion.
Background
Students have been complaining about the long wait times at the cafeteria. I observed and collected data on customer traffic in the cafeteria. The cafeteria is most inefficient during the rush hour, 5:00pm-6:30pm, however breakfast and lunch hours do not experience the same type of rush. The long lines of the pre-cooked meals, interactive meals and cashiers have interrupted service to other areas of the cafeteria such as the drink and the salad bar stations. The data collected during the rush, located in Appendix A, indicates the entrance arrival times of each student, the service time of the cashier, precooked, and interactive lines.
The cafeteria serves about one hundred and fifty residents of Cambridge Hall and approximately one hundred residents from Nottingham Hall. The cafeteria serves hot foods, salads, snacks, sandwiches, and beverages. The data has given me information on the percentage of customers that preferred a hot meal (interactive and precooked) to snacks, the ratio of customers that prefer precooked hot meals over an interactive hot meal, line formation, service times at the different stations, arrival times and the location of the different stations. I also learned that the peak hours of operations are from 5:00 p.m. to 6:30 p.m. and that the cafeteria has two cash registers available but only one is being utilized during the peak hours. If customers decide on a hot meal there is a 2 to 1 ratio that customers will purchase a precooked meal over an interactive meal. Through an informal customer survey, reasonable waiting times were established for the precooked line (5 minutes), the interactive line (10 minutes), and the cashier payment line (1minute). Some of the alternatives that I will propose are to increase in the inter-arrival time, decrease the average service time, decrease the interactive service time, increase the number of cashiers, and decrease the cashier service time For the abovementioned situation, I will determine what changes to the current system are appropriate to both meet management expectations by avoiding major changes and reduce the number of complaints by improving waiting times in the most cost effective way.
Analysis
To evaluate the current situation at the cafeteria, I will use simulation as a decision making model. Simulation deals with what we do not know as opposed to information that we know. Simulation is used because it allows me to test what effect a change will have on a current system before implementing the change, which will save real world time and money. The simulation model strength lies on the capability to replicate a particular situation, in our case, outcomes of various combinations of service times, arrival times and preference of food. In addition, simulation provides better data output than theoretical models available because it uses pseudo-random numbers to repeatedly recreate input data to feed our simulated model, making outcomes more accurate since they are based on ranges rather than averages. Simulation is dependent upon all data being processed as one unit, which is done by establishing the interactions and relationships that the data has. Furthermore, since the computerized designed simulation is based on the situation at hand, situational changes can be made in a more flexible fashion making it easier to analyze them in comparison with previous scenarios.
Beginning with the data legend, the percentage of Hot Food Service (HFS), a ratio of Pre-Cooked orders to Interactive orders, the Inter-Arrival time, Cashier service time, Pre-cooked service time, Interactive service time, and the number of cashiers working are identified. The first column deals with the number of customers, which is set to simulate the probable volume of people entering the cafeteria during the 90 minute rush