ncc case study

National Cranberry Cooperative

Operations Management-SCH-MGMT-670

Catna, Shanmuga

10/17/2014

Operations Management – SCH-MGMT-670

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Introduction

This case analysis looks at the two primary problems at the receiving plant no.1 (RP 1) faced by National

Cranberry cooperative during the cranberry harvesting period, viz. 1) too much waiting period for trucks

before they unload berries at the RP1 and 2) too much overtime costs. There is also a secondary problem

regarding grading of process berries. Half of the berries graded as top quality are actually not top quality and

do not deserve extra premiums paid on the top quality berries.

Problems and Challenges faced by RP1

While there is a stable demand for the cranberries, the production for the cranberries is not stable. The proportion of water harvested cranberries is increasing and likely to stabilize at around 70%.

The plant is incurring high overtime cost

Long waiting hours to unload the crop for growers/owners of the cooperative

Assumptions:

Dumping Capacity

# Kiwanee dumpers 5

Average time to dump 7.5 minutes (max:10, min:5)

Average weight of berries in truck 75 bbls

Total Dumping capacity 5 * 75 * 60 / 7.5 = 3000 bbls/hr

Holding Capacity

Total capacity of bins numbered 1-16 250*16 = 4000 bbls

Total capacity of bins numbered 17-24 250*8 = 2000 bbls

Total capacity of bins numbered 25,26,27 400 * 3 = 1200 bbls

Destoning Capacity

Total de-stoning capacity 4500 bbls / hr

Dechaffing capacity

Total de-chaffing capacity 4500 bbls / hr

Jumbo Separator

# separator units 3 with avg capacity of 400 bbls/hr perunit

Total separator capacity 3 * 400 = 1200 bbls/hr

Bagging Station Capacity

Max. output per day 8000 bbls

Capacity 8000/ 12 = 667 bbls / day

Bulk Bin loading capacity

# loaders for bulk bin loading 4

Total bulk loading capacity 4 * 200 = 800 bbls / day

Bulk Truck loading capacity

# loaders of bulk trucks 2 @ a capacity of 1000 bbls/ hr per unit

Total bulk truck loading capacity 2000 bbls / day


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Process Analysis

We start by making a process flow diagram for the flow of berries at RP1 from the moment berries arrive at

the RP1 in trucks to the moment they leave RP1 after being bagged, bulk loaded into trucks or loaded into

bulk bins.

Process Diagram of Cranberries in National Cranberry Cooperative

•trucks arriving (75 bbls per truck trucks arriving

at RP1

•weighed

weighed, sampled and color graded.

•5 - 10 mins per truck

•5 dumpers

Dumping

1 - 16

•Bins 1 to 16 process dry berries

•Total of 4000 bbls (16 x 250)

17 - 24

•Bins 17 to 24 process dry & wet berries


25,26,27

•Bins 25, 26, 27 process only wet berries


Destoning

4500 bbls total

process only dry berries

Dechaffing

4500 bbls total

process only wet berries

Shipping/ Building

Bailey Mill

Discarded Waste

Bulk bins 800 bbls per hour

Bulk Truck 2000 bbls per hour

Bag 667 bbl per hour

Drying

3 dryers

600 bbls /hr

Separators

1200 bbls

(400 x 3 lines)


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Q1. How might transport vehicles be utilized more effectively? Should crews be scheduled differently on peak days? Be sure to substantiate all calculations.

Start the plant operations at 7:00 AM instead of 11:00 AM.

On Peak days, the employees should come in at 7:00 AM and work eight-hour shifts.

RP1 will not only limit overtime costs, but will also be able to finish the day’s processes without any

backlog and without nearing the 22-hour maximum operating time.

Reduces the total waiting time for all trucks from 511 hours to 127 hours.

Cranberries Delivered Wet

768,600

Dry 1,065,420 Color #1 Color #2 Color #3 Total Pounds Total number of trucks

34,460 401,080 1,398,480 1,834,020 243

From the table above, it can be calculated that:

On a peak day, 18,000 barrels of berries are to be processed and out of which 70% of the berries are

wet. Total number of wet berries on a given peak day 18000 x 70% wet = 12600 bbl/day.

The arrival of berries is evenly distributed over a 12 hour period starting at 7 am.

The delivery load varies from truck to truck @ an average of 75 barrels per truck.

On a peak day, RPI process about 18000 bbl per day spread over 12 hours. Assuming 70% wet, RPI must

process 1050 wet bbl/hour.

18000*0.7/12=1050 wet bbl per hour.

Calculations for Plant Operations Starting at 11:00 AM Looking at the process we know that there is a bottleneck at drying unit. The capacity of the drying unit is 600

bbl /hr which is much lower than the required 1050 wet bbl/day. The trucks start arriving at 7:00 AM and

store the wet berries in storage bins (17 – 24, 25, 26, and 27). The total capacity of these bins is 3x400 + 8 *

250 = 3200 bbls. The trucks start waiting at 10.03 AM (3200 / 1050) (i.e. 3 hours after the receiving unit

starts operating).


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Inventory buildup rate = arrival rate – processing rate = 1050 bbl – 600 bbl 450 bbl / hour.

Total inventory buildup = Inventory buildup between 7 and 11 AM + Inventory buildup after it 11AM

Total inventory buildup = 4200 + 8 * 450 7800

Total wait of the truck is calculated as follows:

At the end of the day (12 hours), there will be 7800 left in the inventory. Out of this 3200 will be in the bins

and 4600 will be waiting in the truck. It will take 4600/600 = 7.67 hours to clear them, So after 2.40 AM the

next morning there won’t be any trucks waiting.

Truck waiting = 7.67 + (12 – 3) 16.67 hours

Waiting time for all tracks adds to 16.67 hours x (4600/2) / 75 511 hours

Overtime Calculations: On peak day: On a peak day a total of 18,000 bbl is received out of which 12600 bbl is wet. At an average processing rate of 600 bbl /hr it will take 21.0 hours to process. Thus, there is an overtime of 13 hours.

In order to reduce the truck waiting time and overtime costs, the transportation schedule or receiving

schedule needs to be utilized effectively. So the Plant operations time should start at 7:00 AM instead of

11:00 AM

Calculations for Plant Operations Starting at 7:00 AM In this scenario, the Inventory buildup rate is arrival rate – processing rate = 1050 bbl – 600 bbl = 450 bbl. At

this rate the wet bins will be filled in 3200/450 = 7.11 hours. So the truck will start waiting at 2:06 PM.

Total wait of the truck is calculated as follows:

At the end of the day (12 hours) there will be 450*12=5400 bbl in inventory. Out of this, 3200 bbl will be in

bins and rest 2200 bbl will be in trucks. It will take 2200/600=3.67 hours to empty the waiting trucks. Thus,

inventory will start building from 7.11 hours to 15.67 hours. So at 10:40 PM there won’t be any trucks

waiting.

Truck waiting = 15.67 – 7 8.67 hours.

Waiting time for all tracks adds to 8.67 hrs x (2200/2)/75 = 127 hours

Overtime Calculations: Even though the plant operation is moved to 7 AM, the over time is still at 13 hours. On a peak day a total of 18,000 bbl is received out of which 12600 bbl is wet. At an average processing rate of 600 bbl /hr it will take 21.0 hours to process. Thus, there is an overtime of 13 hours.


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Q2: Would the installation of a berry grader positively impact the farmers’ income or the cooperative’s?

The installation of a berry grader positively impacts the cooperative’s income, while negatively

impacting the farmers’ income

Currently, the cooperative is overpaying the farmers’ by $112,500 per year due to the fact that half of

the No. 3 berries should actually be graded No. 2B

The installation of a berry grader would positively impact the cooperative’s income, while negatively

impacting the farmers’ income. With the current system, 450,000 bbls of berries are paid a premium of 50

cents per bbl, yet when the berries are used only about half of them are actually considered No. 3’s (berries

with the best color). So basically, the cooperative is paying a premium on 225,000 bbls more than it should

be, and that worked out to about $112,500 in 1970. It would cost the cooperative $10,000 to install a berry

grader, plus the cost of another full-time skilled operator, but it would still impact their income greatly. The

farmers’ would probably prefer that the cooperative continue to grade the color using pictures as a guide,

because they are being paid a 50 cent premium on about half of their No. 3 berries that should actually be

considered No. 2B.

Calculations for savings by installing berry graders

450,000 bbls divided by 50% equals 225,000 bbls.

225,000 bbls at 50 cent each is equal to $112,500 per year

Fixed cost: $10,000 for installation of berry grader

Even though this is a substantial saving, another fact needs to be considered that this is a cooperative

organization. Installing a light grading system would lead to increase in the margins of the receiving plant 1

but would be a loss for the cooperative as a whole as money, instead of being paid to the farmers would go

to the worker who is hired. But status quo can also not be maintained as it leads to wrong distribution of

benefits to farmers with a lower quality crop. An alternate solution can be to have strict control in the

manual grading process and increase the variety of shade cards so that berries can be rightly classified. One

more category in between 2A and 3 can also be 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.


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Q3: What is the purpose of the storage bins? Why do storage bins need to be converted? How many should be converted?

The storage bins are used to hold berries between receiving and destoning and dechaffing.

There will be more water-harvested berries in the next year, so some of the dry barrels need to be

converted to wet barrels.

A total of 19 (out of 27) wet barrels are needed, since there are currently only 11 barrels that can be

used for water-harvested berries that means that 8 of them will need to be converted.

The purpose of the storage bins is to hold the berries between receiving and destining and dechaffing. Some

of the storage bins are for dry berries, a handful of storage bins can be used for either wet or dry berries, and

a few of the holding bins are for wet berries only. Currently, only 11 bins could be used for wet berries, but

the percentage of wet berries will increase from 58% to 70% in the next year. This increase is why some of

the dry berry holding bins need to be converted to be able to hold dry or water-harvested berries. It will cost

$5,000 per bin to convert.

Since only 41% of the barrels can currently be used for water-harvested berries, a certain number will need

to be converted to be able to handle the increase in water-harvest berries in the next year. There are a total

of 27 holding barrels, so at least 70% of them must be able to hold water-harvested berries, or a total of 19 of

the 27 barrels. That means that 8 of the dry holding barrels need to be converted to wet or dry barrels. At a

cost of $5,000 per barrel, that will cost the cooperative $40,000, but it will be worth it to be able to handle all

of the deliveries and cut down on idle time in the following year.

Calculations for converting storage bins to store more wet berries

16 dry barrels, 8 wet/dry barrels, 3 wet barrels

11 out of 27 barrels means that currently 41% can handle wet berries

70% of the 27 total barrels is 19 barrels total that have to hold wet berries

19 barrels (wet barrels needed) minus 11 wet barrels already in use equals 8 to be converted


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Q4: What is the impact of installing one new dryer? 2 new dryers?

Install more drying capacity: Add 1 more dryer

On a peak day a total of 18,000 bbl is received out of which 12600 bbl is wet. At an average

processing rate of 800 bbl /hr it will take 15.75 hours to process. Thus, there is an overtime of 7.75

hours (a saving of 5.25 hours)

Waiting time for trucks: Inventory buildup rate = arrival rate – processing rate = 1050 bbl – 800 bbl =

250 bbl at this rate the wet bins will be filled in 3200/250 = 12.8 hours which is more than 12 hours;

hence there will be no waiting line for the trucks.

Install more drying capacity: Add 2 more dryer

In this case milling area will become the bottleneck which can process 1200 bbl per hour of both wet

and dry. Thus, the effective processing rate will be =1200*0.7=840 bbl per hour

Overtime for each member on average day: On an average day a total of 10,000 bbl is received out

of which 7000 bbl is wet. At an average processing rate of 840 bbl /hr it will take 8.33 hours to

process. Assuming normal working day of 8 hours, there is an overtime of 0.33 hours for each

member of the crew on each average working day. Additional saving is just 0.42 hours.

On peak day: On a peak day a total of 18,000 bbl is received out of which 12600 bbl is wet. At an

average processing rate of 840 bbl /hr it will take 15.00 hours to process. Thus, there is an overtime

of 7.00 hours. An additional saving of 0.75 hours

Given the additional savings from the second dryer are not enough and adding just one dryer solves the

problem of waiting line, it is recommended to go ahead with just one dryer.

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