Use the information in Problem 44 and assuming ship arrivals follow a Poisson distribution and service times follow an exponential distribution. Also, assume that six docks with adequate crane capacity are available. Use a multiple server queuing model to answer the following questions.

a. How many ships are waiting to be unloaded using queuing models?

b. If one ship must remain at one of the six docks for engine repairs for a week after being unloaded, what happens to that week’s system performance? Who suffers from this disruption?

Problem 44 

During the recent pandemic, the seaport in Savannah Georgia, the third busiest in the United States, the seaport averaged loading or unloading 7.6 cargo ships per week. The average time to unload a ship is 1.65 days. Multiple cranes to load and unload the ship operate six days a week.

• How many ships are waiting to be unloaded on average using Little’s Law?

• During the pandemic, at times, demand doubled, how many ships are waiting?

• If demand remains at 7.6 cargo ships per week and through better scheduling, training, and crane operations, the average time to unload a ship lowers to 1.20 days, how many ships are waiting?

• What are possible bottlenecks in this part of the supply chain?