12-23 The Burger Dome waiting line model studies the waiting time of customers at its fast-food restaurant. Burger Dome's single-server waiting line system has an arrival rate of 0.75 customers per minute and a service rate of 1 customer per minute. Adapt the Black Sheep Scarves spreadsheet shown below to simulate the operation of this waiting line. Make sure to use the random values for both interarrival and service times generated in the worksheet 12-23. Assuming that customer arrivals follow a Poisson probability distribution, the interarrival times can be simulated with the cell formula -(1/1)*LN(RAND()), where = 0.75. Assuming that the service time follows an exponential probability distribution, the service times can be simulated with the cell formula -*LN(RAND()), where u = 1. Run the Burger Dome simulation for 1000 customers. Discard the first 100 customers and collect data over the next 900 customers. The analytical model indicates an average waiting time of 3 minutes per customer. What average waiting time does your simulation model show? Round your answer to 3 decimal places. CD E F G H 1 2 3 Black Sheep Scarves with One Quality Inspector Interarrival Times (Uniform Distribution) 4 Smallest Value 0 5 Largest Value 6 7 Service Times (Normal Distribution) 8 Mean 9 Standard Dev 0.5 10 11 12 Simulation 13 14 Interarrival Arrival Service Waiting Service Completion Time 15 Customer Time Time Start Time Time Time Time in System 16 1 14 1.4 1.4 0.0 2.3 3.71 2.3 17 2 1.3 2.7 3.7 1.0 1.5 5.2 2.5 18 3 4.9 7.6 7.6 0.0 2.2 9.8 2.2 19 4 3.5 11.1 11.1 0.0 2.5 13.6 2.5 20 5 0.7 11.8 13.6 1.8 1.8 15.4 3.6 1011 996 2496.8 2498.1 1.3 0.6 2498.7 1.9 1012 997 0.2 2497.0 2498.7 1.7 2.0 2500.7 3.7 1013 998 2.7 2499.7 2500.7 1.0 1.8 2502.5 2.8 1014 999 3.7 2503.4 2503.4 0.0 2.4 2505.8 1015 1000 4.0 2507.4 2507.4 0.0 1.9 2509.3 2.4 1.9 1016 1017 Summary Statistics 1018 Number Waiting 549 1019 Probability of Waiting 0.6100 1020 Average Waiting Time 1.59 1021 Maximum Waiting Time 13.5 1022 Utilization of Quality Inspector 0.7860 1023 1024 Number Waiting> 1 Min Probability of Waiting > 1 Min 393 0.4367 2.111 minutes a. One advantage of using simulation is that a simulation model can be altered easily to reflect other assumptions about the probabilistic inputs. Assume that the service time is more accurately described by a normal probability distribution with a mean of 1 minute and a standard deviation of 0.2 minutes. This distribution has less service time variability than the exponential probability distribution used in part (a). What is the impact of this change on the average waiting time? Round your answer to 3 decimal places. 1.040 minutes