11BM60008 Sec B National Cranberry Cooperative

N ati atio ona nall Cranberry Cranberry Co Coo ope perati rativ ve - A Case Study Production Production and Operation Operation Manage Management ment Ass Assignment

Submitted by: Kunal Verma (11BM60008) VGSOM

Vinod Gupta School of Management IIT Kharagpur

Nationall Cranberry Cooperative Nationa

About this Document Purpose The purpose of this document is to provide pr ovide the solution to the National Cranberry Cooperative Case problem. Intended Audience This document will help: Students and instructors to provide the various details regarding the National Cranberry Cooperative Case for Production and Operations Management Assignment.



Introduction - Process Analysis We start by making a process flow diagram diag ram for the flow of berries at RP1 from the moment berries arrive at the RP1 in trucks to the moment they leave in RP1 after afte r being bag packed, bulk loaded into trucks t rucks or loaded into bulk tins.

Fig 1: Process Flow Diagram Vinod Gupta School of Management IIT Kharagpur


Assumptions and Data: The capacities of the various processes are based on the assumptions or data as shown below: Dumping Capacity Number of Kiwanee Dumpers = 5 Average time taken by truck to load the berries onto Kiwanee Dumpers = 7.5 minutes (Maximum being 10 and minimum being 5 minutes) Average weight of berries in a truck = 75 bbls. Dumping Capacity = 5 * 75 * 60 / 7.5 = 3000 bbls/hr. Holding Bin Capacities Bin No. 1-16 can hold dry berries only up to 250 bbls per bin. Total capacity of bin numbered 1-16 = 250*16 = 4000 bbls Bin No. 17-24 can hold dry/w d ry/wet et berries up to 250 bbls per bin Total capacity of bin numbered 17-24 = 250*8 = 2000 bbls. Bin No. 25-27 can hold wet berries up to 400 bbls per bin Total capacity of bin numbered 25-27 = 400*3 = 1200 bbls. De-stoning Capacity No. of de-stoning units = 3 Capacity of each unit = 1500 bbls/hr b bls/hr Total de-stoning capacity = 4500 bbls/hr bb ls/hr



De-chaffing Capacity No. of de-chaffing units = 3 Capacity of each unit = 1500 bbls/hr b bls/hr Total de-chaffing capacity = 4500 bbls/hr Jumbo Separator and Bailey Mill Lines No. of separator units = 3 Average capacity of each unit = 400 bbls/hr Total separator capacity = 1200 bbls/hr Bagging Station Capacity Maximum output per day = 8000 Working hours = 12hrs. Capacity = 8000/12 = 667 bbls per day Bulk Bin Loading Capacity No. of loaders for bulk bin loading = 4 Capacity of each loader = 200 bbls/day b bls/day Total bulk bin loading capacity c apacity = 4 * 200 = 800 bbls per day. Bulk Truck Loading Capacity No. of loaders of bulk trucks = 2 Capacity of each loader =1000 bbls/hr bb ls/hr Total Capacity Bulk Truck loading Capacity = 2000 bbls/hr



Installing a Light Grading System As given, out of a total of 4, 50,000 bbls of berries graded as top quality only half were top quality and deserved the 50 5 0 cent per bbl bb l premium. The light grading system which would accurately grade the berries would save 4, 50,000*0.5/2 = $1,12,500 per season at one time investment of $10,000 and recurring rec urring cost of hiring a skilled operator at $10,000 (Assumed)...This would lead to a substantial saving. But another fact nee ds to be considered that this is a cooperative organization. Although installing a light grading system would lead to increase in the margins marg ins of the receiving plant 1 but would be loss for the cooperative as a whole as money instead of being b eing paid to farmers would go to worker who is hired. But status quo can also not be maintained as it leads to wrong distribution of b enefits to farmers with a lower quality qua lity crop. An alternate solution can to be stricter in the m anual grading process and increasing the variety of shade cards so that berries can be rightly rightl y classified. One more category in between 2A and 3 can also made having a lesser premium than quality 3. But the various other implications of this step should be taken into account like increased final processing cost and resentment from the farmers.

Decreasing the truck waiting time Assume work day has 11 hours We know 70% of the total berries received are wet. Total wet berries per hour = 1200bbls (20000/11)*0.7 3 dryers can handle 600 bbls/hr On an average day if 10000 bbls are received per day number of wet berries received would be 7000 so number of dryer hours required are 7000/600 = 11.7 hrs Actual no. of dryer hours available are 8 s o 11.7-8 = 3.7 hours of overtime should be paid to workers. On a peak day if 20000 bbls are received per day number of wet berries received would be 14000 so number of dryer hours required are 14000/600 = 23 hrs Actual no. of dryer hours available is 8 so 23-8 = 15 hours of overtime should be paid to workers. We also know dumpers operate at a t 1209 bbls per hour (19000*0.7/11) Inventory build up rate is 1209-600 = 609 bbls per hour We have total capacity of 3200 bbls Hence the total area where inventory inventory is kept is full full in 5.25 hours (3200/609) Queue of trucks start forming after 5.25 hours of operation Vinod Gupta School of Management IIT Kharagpur


At the end of 11 hours we have 6699 bbls of berries to be stored (609*11) out of which 3499 are waiting in trucks and 3200 are in inventory area. We also know one truck has 75bbls of berries so we have total to tal 47 trucks (3499/75) in waiting which will take 5.83 hours (3499/609) to clear. Total time spent by truck drivers to unload is 270 hours (5.8*47) Labor overtime cost is 3.7*27*1.5*13for 10k bbls

Labor overtime cost for 20k bbls is 14.2*27*1.5*13+14.2*26*1.5*8 14.2*27*1.5*13+14.2*26*1.5*8 This can be summarized as 10000 bbls

20000bbls

11.7

23

Plant operating hours

8

8

Truck hours waiting

0

270

Truck waiting cost(in $)

0

27000

3.7

14.2

1948.05

11906.7

Dryer hours

Labor waiting time Labor waiting cost(in $) Table 1

Now let us analyse various options that th at we have Solution 1 - Increase number of dryers by 1 New dryer capacity is 800 bbls/hr Labor overtime cost is 0.75*27*1.5*13= 394.875 Labor overtime cost for 20k bbls is 9.5*27*1.5*13+9.5*26*1.5*8=7965. 9.5*27*1.5*13+9.5*26*1.5*8=7965.75 75 Vinod Gupta School of Management IIT Kharagpur


This can be summarized as 10000 bbls

20000bbls

8.75

17.5


8

8

Truck hours waiting

0

54


0

5400

0.75

9.5

Labor waiting cost(in $)

394.875

7965.75

Cost of additional dryer

60000

60000

Dryer hours

Labor waiting time

Table 2 Total savings (1948.05+11906.7)-(394.875+7965.75) = 5494.125 We have return on investment investment 5494/60000*100 =9.2%

Solution 2 - Increase number of dryers by 2 New dyer capacity is 1000 bbls/hr Labor overtime cost is 0 in case of 10k bbls Labor overtime cost for 20k bbls is 6*27*1.5*13+6*26*1.5*8=2187.9 6*27*1.5*13+6*26*1.5*8=2187.9 in case of 20k bbls This can be summarized as

10000 bbls

20000bbls

Dryer hours

7

14


8

8



Truck hours waiting

0

0


0

0

Labor waiting time

0

6


0

11666.85

120000

120000

Cost of 2 additional dryer Table 3 Total savings (1948.05+11906.7)-(2187.9) = 11666.85 Return on Investment 11666.85*100/120000 11666.85*100/120000 =9.75

Option 2: Converting Dry bin into bins that can be used for both dry and wet bins

10000 bbls

20000bbls

Bins used for dry berries

7

14


8

8

Truck hours waiting

0

0


0

0

Labor waiting time

0

6


0

11666.85

120000

120000

Cost of 2 additional dryer



11BM60008 Sec B National Cranberry Cooperative

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