ISEN $415$

Simio Final Project

Due $12/10/2023$ midnight, This is a hard deadline, No exception will be made Each team can have a maximum of $3$ members. Working individually is also allowed.

Submit your group simio file spfx to blackboard $($one group only needs one team member to submit$)$ Use Floating label in Drawing tab in Simio to write down your team member's names

Consider a restaurant where customers come to have meals. Customers can either have ordered online ahead of time and come at a later time to pick up their orders or they can walk in to have meals inside the restaurant. Online orders are handled directly by the kitchen where cooks prepare the meal and leave the packaged meal in a bin outside of the kitchen.

Historical records show that approximately $69\%$ of customers have ordered online ahead of time and the times for a cook to prepare a meal are triangularly distributed with parameters $(5,10,15)$ minutes. If an arriving customer has ordered online already, a cashier retrieves the packaged food from the bin and processes the customer's payment. Historical records also estimate that the times required for the cashier to retrieve the food and process the payment are triangularly distributed with parameters $(2,4,0)$ minutes. If an arriving customer has not ordered ahead of time, the cashier processes payment and sends the order to the kitchen. The distributions of the cashier times and cook times are the same as for the online$-$ordered customers $($triangular $(2,4,6)$ and triangular $(5,10,15),$ respectively$).$ The restaurant has a maximum of $30$ seats. The dinning$-$in time follows uniform distribution with parameters $(10,20)$ minutes. If it is full, walk$-$in customers will leave directly. Onlineordered customer amival rates vary during the day as do the cook staffing levels. The table below gives the arrival the arrival rate for the "Cashier" is the cashier number and "Cooks" is the cooks' number in the kitchen, A$1$ is the arrival rate for the online orders, and $A2$ is the arrival rate for customers.

$\backslash$table$[[$Time$-$Period,Cashier,Cooks,Al$,$A$2],[8$:$00$ am$-11$:$00$ am$,1,3,12,12],[11$:$00$ am$-3$:$00$ pm$,3,4,20,20],[3$:$00$ pm$-7$:$00$ pm$,3,5,30,15],[7$:$00$ pm$-10$:$00$ pm$,1,2,15,12]]$

Q$1$: Build a simio model for this restaurant and use different colors to distinguish different customer types. $(40$ points$)$

Q$2$: Assume the restaurant opens at $8am$ and closes at $10pm.$ You can ignore the customers that are still in the system at closing time. Set total run time for $1$ day and insert time plot for instantaneous number in the system. Use the status label to show how many customers have left due to the lack of seats. $(20$ points$)$

Q$3$: Performance metrics of interest include the average time customers spend in the system, average customer number in the system, and utilization ratio of the cashier and kitchen. Use $100$ replications to generate SMORE plots for the performance metrics of interest. $(30$ points$)$

Q$3$: Create a reference comparison of simulations when the maximum seat number is $10,30,50,$ and $70.(10$ points$)(10$ points$)$