National Cranberry Cooperative (NCC) Case Study Report.doc

L6116 team members: Jia Hao, Abhishek Karmakar, Zhichao Peng, Devang Shah, Jun XieNational Cranberry Cooperative Case StudyOn February 14, 1971, Hugo Schaeffer, the vice president of operations at National Cranberry Cooperative (NCC) is reviewing the previous years process of fruit operations at receiving plant 1 (RP1). He states that they still have high overtime costs, despite spending $75,000 on a new dumper. Trucks are still having to wait to unload fruit at the receiving plant. This report will analyze the current state of RP1, analyze Wallistons recommendations, and provide justification for implanting the recommendations.In appendix A, a process flow chart is included to describe the process both dry and wet berries go from receiving to shipping. A few assumptions were to be made before beginning to solve the problem. The assumptions that were made for this problem are:1. An average of 18,000 bbls of berries received on the peak day.2. On the peak day, working hours were capped at 12 hours.3. 58% of the berries received on the peak day were wet berries.4. A constant rate of 200 bbls/hour for each machine in the drying process.5. A constant rate of 400 bbls/hour for each machine in the separation process.Using these assumptions, calculations were made for the capacity of the bins and each process. These values were used to determine the bottleneck of the process, since the bottleneck will give us an indication of which process is the slowest and causing the delays for the trucks.1. Total number of wet berries received/day: 18,000 bbls * 0.58 = 10,440 bbls/day.Total number of wet berries received/hour: 10,440 bbls / 12 = 870 bbls/hour.2. Mixed berry bin capacity: Bins 17-24, total of 8 bins * 250 bbls/bin = 2,000 bbls/bin.Wet berry bin capacity: Bins 25-27, total of 3 bins * 400 bbls/bin = 1,200 bbls/bin.Total capacity for wet berries/day: 2,000 + 1,200 = 3,200 bbls/day.3. Dechaffing process rate: 1,500 bbls/hour * 3 machines = 4,500 bbls/hour.4. Drying process rate: 200 bbls/hour * 3 machines = 600 bbls/hour.5. Separation process rate: 400 bbls/hour * 3 machines = 1,200 bbls/hour.6. Bagging process rate: 666.67 bbls/hour.7. Bulk truck process rate: 1,000 bbls/hour * 2 stations = 2,000 bbls/hour.8. Bulk storage process rate: 200 bbls/hour * 4 stations = 800 bbls/hour.Based on the above assumptions and calculations, it was concluded that the drying process is the bottleneck for this plant. Therefore, the drying process would need to be improved, or, the bins need to be converted to handle higher capacity to prevent the inventory building up higher than the actual capacity of the factory.In this case, the two constraints that were to be adjusted were the number of drying machines, and the capacity or number of bins. We took into consideration the number of machines and capacity of bins to come up with a solution for this problem. The increasing of number of drying machines to one more was already suggested by Walliston, as well as increasing the capacity of the bins. Increasing the capacity of bins would be a cost effective way of reducing the wait times for the trucks.The inventory buildup diagram for the current state is shown below:Figure 1: Inventory Buildup Diagram for the Current StateFrom figure 1, it is clear that there is a long waiting time for the trucks from around 11am to 11pm. The above diagram limits the level at 3,200 bbls since that is the capacity of the factory to hold berries. The two alternatives that were suggested were:1. Install two new dryers, and convert 6 dry bins to hold mixed berries. Cost of converting 6 dry bins to mixed bins = 6 * $5,000 = $30,000. Capacity of 6 dry bins from bins 1-16 to hold mixed berries: 6 * 250 = 1,500 bbls, so the total capacity increases by 1,500 bbls to 4,700 bbls/day. The cost of adding two new dryers: 2 * $25,000 = $50,000. Increased process rate of: 2 * 200 = 400 bbls/hour, so the total drying process rate increases from 600 bbls/hour to 1,000 bbls/hour. Total investment cost = $30,000 + $50,000 = $80,000.2. Install one new dryer, and convert 12 bins to hold wet berries. Cost of converting 12 dry bins to mixed bins = 12 * $5,000 = $60,000. Capacity of 12 dry bins from bins 1-16 to hold mixed berries: 12 * 250 = 3,000 bbls, so the total capacity increases by 3,000 bbls to 6,200 bbls/day. The cost of adding one new dryer: 1 * $25,000 = $25,000. Increased process rate of: 1 * 200 = 200 bbls/hour, so the total drying process rate increases from 600 bbls/hour to 800 bbls/hour. Total investment cost = $60,000 + $25,000 = $85,000.By converting 6 bins to hold mixed berries, the total holding capacity of the factory increases to 4,700 bbls/day. With the increased capacity of adding two new dryers, figure 2 below shows the inventory buildup diagram for the first proposed solution:Figure 2: Inventory Buildup Diagram for Solution 1Converting 12 bins to hold mixed berries, the total holding capacity of the factory increases to 6,200 bbls/day. With the increased capacity of adding two new dryers, figure 3 below shows the inventory buildup diagram for the second proposed solution:Figure 3: Inventory Buildup Diagram for Solution 2Both of these solutions are feasible and completely eliminate the waiting time for trucks. However, solution 2 requires the factory to run longer than solution 1. To be able to make a fair comparison of both these solutions, the wage costs had to be considered as well. The investment cost for solution 1 is $80,000 and the investment cost for solution 2 is $85,000. We assumed the costs or running the factory during regular hours was the same, so overtime costs had to be calculated to make a fair comparison.Assuming a total of 53 workers during the high volume period, out of which 2 are working in the control room as operators, we have left 51 full time workers who are paid $3.75/hour and any extra part time workers are paid $2.25/hour.1. Overtime costs for solution 1: Receiving department working 4 hours overtime: 4 hours * $3.75 * 1.5 * 15 workers = $337.5 Part time workers working 5 hours overtime: 5 hours * $2.25 * 1.5 * 26 workers = $438.75 Full time workers working in destoning, dechaffing, drying, milling, and shipping: 5 hours * $3.75 * 1.5 * 10 workers = $281.25 Total overtime cost per day = $1,057.5 Total overtime cost per high season per year = $1,057.5 * 101 days = $106,807.5/year2. Overtime costs for solution 2: Receiving department working 4 hours overtime: 4 hours * $3.75 * 1.5 * 15 workers = $337.5 Part time workers working 8 hours overtime: 8 hours * $2.25 * 1.5 * 26 workers =