Customer into categories to level the office workload

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An office that dispenses automotive licenses plates has divided its customer into categories to level the office workload. Customers arrive and enter one of three lines based on their residence location. Model this arrival activity as three independent arrival streams using an exponential inter-arrival distribution with mean 10 minutes for each stream, and an arrival at time 0 for each stream. Each customer type is assigned a single, separate clerk to process the application forms and accept payment, with a separate queue for each. The service time is UNIF (8, 10) minutes for all customer types. After completion of this step, all customers are sent to a single, second clerk who checks the forms and issues the plates (this clerk serves all three customer types, who merge into a single firstcome, first-served queue for this clerk). The service time for this activity is UNIF (2.66, 3.33) minutes for all customer types. Develop a model of this system and run it for 5,000 minutes, observe the average and maximum time in system for all customer types combined. A consultant has recommended that the office don’t differentiate customers at the first stage and use a single line with three clerks who can process any customer type. Develop a model of this system, run it for single replication of 5,000 minutes, and compare the results with those from the first system. Put text boxes in your Arena files with numerical results requested.

Reference no: EM131232330

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