Parts arrive at a single workstation system according to an exponential interarrival distribution with mean 21.5 seconds: the first arrival is at time 0. Upon arrival, the pans are initially processed. The processing-time distribution is TRIA(16, 19, 22) seconds. There are several easily identifiable visual characteristics that determine whether a pan has a potential quality problem. These parts, about 10% (determined after the initial processing), are sent to a station where they undergo a thorough inspection. The remaining parts are considered good and are sent out of the system. The inspection-time distribution is 95 plus a WEIB(48.5, 4.04) random variable, in seconds. About 14% of these parts fail the inspection and are sent to scrap. The parts that pass the inspection are classified as good and are sent out of the system (so these parts didn't need the thorough inspection, but you know what they say about hindsight). Run the simulation for 10,000 seconds to observe the number of good parts that exit the system, the number of scrapped parts, and the number of parts that received the thorough inspection. Animate your model. Put a text box in your model with the output performance measures requested, and make just one replication.