# Om Cranberry Case

Essay by   •  February 15, 2017  •  Case Study  •  2,275 Words (10 Pages)  •  3,479 Views

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## Group 1

Lyn , Bonus , Taew , Kento , Kevin

## Case Report: National Cranberry Cooperative

1. Mark the capacity (C) and implied utilization (U) of each resource in the process flow diagram below. Detail the calculation of capacity and implied utilization for two resources of your choice.  Mark the maximum contents of the bins. [2 points]

[pic 1][pic 2]

Bulk and Bag

Separators

C = 1200bbls/hr        U = (1440/1200) =120%

Dryers

C = 600 bbls/hr U = 180%

Destoners

C =4500bbls/hr ,U = 8%

Kiwanee Dumpers

C = (600*5) =3000bbls/hr        U = (1440/3000) = 48%

Trucks in

Queue

Bins 1-16

storage = 4540004000bbls

Bins 17-27

storage = 3200 bbls

Dechaffers

C = 1500 bbls/hr U = 24%

Dry berries

360 bbl/hr

Wet berries

1080  bbl/hr

Dechaffers

C = 3000 bbls U = 36%

Calculation of the two resources

• Kiwanee dumpers                                 5

Average time to dump                        7.5 minutes/truck

Average weight of berries in truck         75 bbl/truck

Total dump capacity                        5*75*(60/7.5) = 3000 bbl/hr

Implied utilization                                (360+1080)/3000 = 48%

• Dechaffers                                        3

Capacity: 1 for dry berries                         1500 bbl/hr

2 for wet berries                         1500 bbl/hr*2 = 3000 bbl/hr

Implied utilization

1 for dry berries                         360/1500 = 24%

2 for wet berries                        1080/3000 = 36%

Maximum contents of the bins

- Dry berries

Bin 1-16: 250 bbl.each                         16*250 bbl = 4000 bbl

- Wet berries

Bin 17-24: 250 bbl each:                         8*250 bbl = 2000 bbl

Bin 25, 26, 27: 400 bbl. each                3*400 bbl = 1200 bbl

Total contents for wet berries are 3200 bbl.

Total contents of the bins                4000 + 2000 + 1200 = 7200 bbl

1. On a busy day, what is RP1’s current maximum hourly throughput rate?

The current maximum hourly throughput rate is 960 bbl/hour for RP1.

• 600 + 360 = 960 bbl/hour

We can see in the diagram for question 1 that the bottleneck for wet berries is the dryers. Logically the throughput rate for wet berries is therefore 600 bbl/hour. On the other hand the maximum throughput rate for the dry berries is 300 bbl/hour during the separating process because the demand rate is lower than the capacity rate of every dry berry process.

• 1200 * 0.25 = 300 bbl/hour
[a]

For the dry berries, the throughput rate is 360 bbl/hour. Although the capacity of the separator of the dry berries is 300 bbl/hour (1200 bbl/hour * 0.25 = 300 bbl/hour), the wet berries do not consume all the leftover 900 bbl, to be specific 600 bbl/hour. Thus, the separator can handle all 360 bbl/hour of dry berries.

1. Using  the  information  described  in  the  case  (and  below),  present  the  situation during a busy day by constructing an inventory build-up diagram for bins and trucks. Mark the bin inventory and truck inventory clearly.

Arrivals:

Total berries                 = 17280 bbl (from 7am to 7pm)

Average berries         = 1440 bbl/hr

Wet berries (75%)         = 1440 * 0.75         = 1080 bbl/hr

Dry berries (25%)         = 1440 * 0.25         = 360 bbl/hr

The RP1 starts the operation at 7 am.

Since the dry berries are limited by demand constrained, all 360 bbl/hr will be processed. However, the wet berries capacity is limited at 600 bbl/hr while the demand is 1080 bbl/hr. The total inventory build up will be 12*(1080-600) = 5760 bbl. It will need 9.6 hours to finish them.

Considering the bins, the bins 17-27 will be full after 3200/(1080-600) = 6.67 hour. It will be full until 7pm which is the time the truck stop arriving. The bins will need 3200/600 = 5.33 hours to complete.

Considering the trucks, the truck will not be able to dump if the bins are full. In this case, the dry berries bins (bins 1-16) will not be full but the wet berries ones (bins 17-27) will be full. After 6.67 hour, trucks have to line up and wait to dump the wet berries. In this case the truck will have the inventory = (12-6.67) hour * (1080-600) bbl/hr = 2560 bbl. It will take 2560/600 = 4.27 hours to empty the truck.

The inventory diagram is as below

[pic 3]

• At 7am, the bins inventory starts to raise up with the slope 480 bbl/hr. At 13:40pm, the wet berries bins 17-27 are full. The bins inventory reaches its maximum and maintains until 11:16pm, the bins inventory starts to reduce with the rate 600 bbl/hr.
• At 13:40pm, since the wet berries bins are full, the trucks have to wait. The truck inventory increases at the rate 480 bbl/hr. The truck inventory continues until 7pm which is the time the truck stop loading. The maximum truck inventory is 2560 bbl. After 7pm, the truck inventory start dropping with 600 bbl/hr rate. At 11:16pm, all trucks will be empty. All 2560 bbl are fed to the RP1.
• After 11:16pm, the bins inventory will decline at the rate of 600 bbl/hr and complete all wet berries at 4:36am in the next day.
• The total inventory inclines from zero at 7am with 480 bbl/hr slope and reaches its peak at 7pm with 5760 bbl inventory. After 7pm, the total inventory fall down with 600 bbl/hr and be empty at 4:36am.
1. Quantify  the  costs  and  benefits  of  two capital  investments:  the  fifth  Kiwanee dumper  purchased  in  1995 and light meter. What  recommendations  would  you  make  to Mr. Schaeffer?
• The Investment of the fifth Kiwanee dumper did not pay off because it did not increase the capacity of the overall process. The bottleneck is at the dryer process. Adding the fifth Kiwanee dumper did not generate more revenue or save time.
• In 1995, the \$1.50 premium was paid on about 450,000 bbls of berries but indeed half of them were not color #3. The cost saving from light meter installation will be = 50% * 450,000 bbl * \$1.5 = \$337,500.
• The system costs \$40,000 and requires a full-time skilled operator.
• The operator works from 7am to 11:16pm (Until all trucks finish unloading). If we hire 2 shifts of operators, working 22 days/week. The labor cost is roughly 22 days/month * 3 months * \$13/ hour* 8 hours/shift * 2 shifts = \$13,728. The system cost and the labor cost worth the investment in the light meter.
• We would recommend Mr. Schaeffer to install the light meter aiding in color grading and hire two full-time operators to control the system. The investment will be 40,000 \$ which is a one-time investment and the labor cost roughly less than 20,000 \$/year. The light meter save the cost about 337,500 \$/year.

Extra  credit (up to 2  points): Do Question  4  (cost-benefit  analysis) for  bins  conversion and/or more dryers. Please specify the best number of bins to convert and/or dryers to buy in your recommendations.

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