Assignments

$1.$ Modify your simulation model of the current policy so that a new customer will balk with a probability of $0\mathrm{.}6$ if there are $4$ or more customers in the first three stations. Explain how you implement this balking logic and provide snapshots of your add$-$on process and its steps. Evaluate the performance of the system with respect to the utilization of the servers, expected number of customers in the system, the time that customers spend in the system on average, percentage of customers that balk, and the average time in system per customer type.

$2.$ Consider the following manufacturing system that processes two different part types $(\backslash ($ A $\backslash )$ and $\backslash ($ B $\backslash )).$ The arrival rates are $12$ parts$/$hr for $\backslash ($ A $\backslash )$ and $20$ parts$/$hr for $\backslash ($ B $\backslash )($both arrival processes are Poisson$).$ Server processing times are triangularly distributed with parameters shown in the table below.

Parts that are processed more than once on the Grind machine will have a higher priority at the Package station. On the other hand, parts that are routed back to the Grind machine more than three times are deemed "bad" and will be scrapped. Develop a Simio model of this manufacturing system and estimate at steady state the average time in system per part type, average time in system for all parts, and percentage of scrapped parts. Perform model verification $($using animation and also comparison with queueing results$).$ Use State Assignments so that entities will change colors as they leave each station, i$.$e$.,$ default green for type $\backslash ($ A $\backslash )$ and blue for type $\backslash ($ B $\backslash )$ after being created, red once processed on Machine, and black after leaving the Grind station $($parts that are reworked on the Grind machine must maintain their original color$).$ Justify your run configurations $($run length, number of replications, and warm$-$up period$)$ using the SMORE plots.