Use an ARENA simulation model to answer

An automated assembly line receives parts of three types: A, B and C. These parts receive treatment on a single machine and then they leave the system. There are three sets of machines (each set has four identical machines). Set #1 has machines from 1 thru 4. Set #2 has machines numbered from 5 to 8, and Set #3 has machines numbered from 9 to 12. Parts type A can go only to machines from set #1, while parts type B can go to any machine from the second set. Finally, parts type C can go to any machine from the third set. Operation times on each part are uniformly distributed between 0.5 and 1.5 hour. (Remember that parts are worked on just one machine, and then they leave the assembly line). Machines from the three sets require frequent adjustments. Times between adjustments for machines from set #1 are triangular distributed with maximum, minimum, and most frequent values as 5, 1, and 4 respectively. Times between adjustments for machines from set #2 are uniformly distributed between 2 and 3 hours. And Times between adjustments for machines from set #3 are normally distributed with mean 1.8 hours and variance equal to 0.25 hours2. The assembly line has a team of technicians performing the adjustments of the machines. The team works two 10-hour shifts per day. During the first shift there are 4 technicians available, and during the second shift there are only 3 technicians. It takes one technician between 1.5 and 3 hours (uniformly distributed) to adjust a machine; only one technician can be assigned to work on a machine even if the other technicians are idle. If at any given time there are more machines needing adjustments than available technicians, they form a (virtual) FIFO repair queue and wait for the first available technician. A technician works on a machine until it is adjusted (even at the expense of having to stay longer during its shift this extra-time is not paid during the next shift, that is, if a technician had to stay longer one day, he-she still has to work his-her 10-hour shift), regardless of what else is happening in the system. All uptimes and downtimes are independent of each other. Starting with all machines at the beginning of an up time, simulate this for 500 hours and obtain the following data: 1. (25%) The time-average number of machines that are down (in repair or in the queue for repair). Put your results in a Text box in your model. 2. (25%) The average scheduled utilization of the technicians as a group. Put your results in a Text box in your model 3. (25%) Maximum time that a machine needed to wait for a technician in order to be adjusted. Put your results in a Text box in your model 4. (25%) Plot the total number of machines down (in repair plus in queue) over time.