1. Develop an MPS schedule, that includes Available to Promise, based on the forecast and order data provided. 2. Develop a rough-cut capacity plan based on the MPS schedule and the data provided. 3. Discuss any issues that you notice based on the two plans that you have developed. Also, if you were to tweak your production schedule to work around some of the constraints, how would you do that?| Run Time (per item, in minutes) Setup Time (per lot) Lot Size (minimum) qty. Model On-hand A 3.7 90 minutes 150 10 B 5.1 40 minutes 100 0 4.3 60 minutes 120 0 D 8.4 200 minutes 350 22 E 11.2 120 minutes 400 153 4 Model Weeks 1 2 3 4 5 6 7 oc 9 10 Forecast 45 45 45 45 45 45 45 45 45 45 53 41 22 15 4 7 2 0 0 0 Customer Orders Forecast B 35 35 35 35 35 35 35 35 35 35 66 40 31 30 17 6 2 0 0 0 Customer Orders Forecast 50 50 50 50 50 50 50 50 50 50 52 43 33 21 14 4 7 1 0 0 Customer Orders Forecast D 180 180 180 180 180 180 180 180 180 180 277 190 178 132 94 51 12 7 9 2 Customer Orders Forecast E 200 200 200 200 200 200 200 200 200 200 223 174 185 109 74 36 12 2 0 0 Customer Orders 1. Develop an MPS schedule, that includes Available to Promise, based on the forecast and order data provided. 2. Develop a rough-cut capacity plan based on the MPS schedule and the data provided. 3. Discuss any issues that you notice based on the two plans that you have developed. Also, if you were to tweak your production schedule to work around some of the constraints, how would you do that?| Run Time (per item, in minutes) Setup Time (per lot) Lot Size (minimum) qty. Model On-hand A 3.7 90 minutes 150 10 B 5.1 40 minutes 100 0 4.3 60 minutes 120 0 D 8.4 200 minutes 350 22 E 11.2 120 minutes 400 153 4 Model Weeks 1 2 3 4 5 6 7 oc 9 10 Forecast 45 45 45 45 45 45 45 45 45 45 53 41 22 15 4 7 2 0 0 0 Customer Orders Forecast B 35 35 35 35 35 35 35 35 35 35 66 40 31 30 17 6 2 0 0 0 Customer Orders Forecast 50 50 50 50 50 50 50 50 50 50 52 43 33 21 14 4 7 1 0 0 Customer Orders Forecast D 180 180 180 180 180 180 180 180 180 180 277 190 178 132 94 51 12 7 9 2 Customer Orders Forecast E 200 200 200 200 200 200 200 200 200 200 223 174 185 109 74 36 12 2 0 0 Customer Orders