IDS 532 Introduction to Operations
Management
National Cranberry Cooperative
Case Analysis
Abhishek Yadav
Manfred Gaisie
Saijanane Balasubramanian
Savitha Tamraparni-Vittal
Srija Gupta
UIN: 655422585
UIN: 650179685
UIN: 654990182
UIN: 662405004
UIN: 656331239
1. Draw the process flow diagram of the process fruit operation at Receiving Plant #1 (RP1). (10
points)
Answer
Kiwanee Dumpers
Number of Dumpers =5
Time taken to load a
truck : 7 - 8minutes
Capacity=(5*75*60)/7.5
=3000bbls/min = 50
bbls/hr
Fruit Processing
Trucks Arriving
75 bbls/hr
(Weighed, Sampled,
Colored, Graded)
Bins 1-16-Only
dry berries.
16*250=4000bbls
Bins 17-24-Both
dry & wet berries.
8*250=1000bbls
Bins 24-27-Only
wet berries.
3*400=1200bbls
Drying
Capacity=
3*200=600bbls/hr
Dechaffing
Capacity=
3*1500=4500bbls
(Only wet berries)
Destoning
Capacity=
3*1500=4500bbls
(Only dry berries)
Bagging
Station
Separators
Capacity=
3*400=1200bbls
Bulk Bin
Station
Bulk Truck
Station
2. Is the process at RP1 machine-paced or worker-paced? (2 points)
Answer
The process at RP1 can clearly be stated as machine-paced process since it is highly mechanized
depending on the pace of the conveyer belts. It involves specific operations such as receiving and testing
of fruits, temporary holding, destoning, dechaffing, drying, separation, bulking and bagging of cranberries.
The objective of the Receiving Plant, i.e., RP1 was to gather the bulk berries and prepare them for storage
and processing into frozen fresh berries, sauce and juice. These processes are carried out in a steady pace
independent of the surroundings of the plant with no human interference and hence can be concluded to
be a machine-paced process.
3. Which operation(s) is the bottleneck? (3 points)
Answer
Process Capacity
Process 1: Dumping
The average truck delivery is 75 bbls/hour and it takes close to 7 to 8 minutes for a truck to empty the
berries into the bins, considering the average to be 7.5 minutes, the flow rate is 10 bbls/minute into a bin
using Little’s Law. Thus, the flow rate for an hour would be 600 bbls/hour.
Since there are five Kiwanee dumpers, the flow rate would be 3000 bbls/hour
Therefore, Process Capacity = 3000 bbls/hour
Process 2: Dechaffing
This process is not considered since dechaffing is carried out dry berries but NCC is interested in wet
berries in this particular case study.
Process 3: Drying
Rate of drying = 200 bbls/hour
Number of drying units = 3
Thus, Process Capacity = 200 * 3
= 600 bbls/hour
Process 4: Quality Grading – Separation of berries
Rate of separation = 400 bbls/hour
Number of separation units = 3
Thus, Process Capacity = 400 * 3
= 1200 bbls/hour
Rate of separation of reduces from 450 bbls/hour to 400 bbls/hour as the percentage of bad fruit increases
and the average effective capacity is assumed to be 400 bbls/hour.
Drying is the bottleneck since the process which has the least capacity is considered to be the bottleneck
having a processing capacity of 600 bbls/hour.
4. What are the main problems faced by RP1? (2 points)
Answer
The following could be some of the major problems faced by Receiving Plant 1:
I.
II.
III.
IV.
The waiting time or the queue time for the trucks to unload the berries into the Kiwanee dumpers
is long. The average truck delivery rate is 75 bbls and it takes close to 7 to 8 minutes for each truck
to finish unloading the berries into the dumpers. The wait periods for the trucks is unknown and
this made the berry growers upset as their leased trucks with hired drivers sat idle.
The berry grading process between grades 2B and 3 berries is inaccurate. Whenever there is a
situation to grade the berries between 2B or 3, the chief berry receiver usually graded it a 3. In
1995, the $1.50 premium was paid on about 450,000 bbls. When these berries were later used, it
was found that only half of them were grade 3 berries which led to a notable loss of price paid.
The overtime of RP1 is unknown because of long queue times for trucks to unload berries into
the Kiwanee dumpers.
The holding bins for wet berries is less when compared to dry berries which increases the
processing time at every stage.
5. How much overtime is required during peak season? (5 points)
Answer
Considering calculations from Exhibit 1 on September 23, 1995 which happens to be one of the days
during the peak season, the following calculations are carried out to arrive at the overtime for peak
season:
Flow Rate = Minimum {Demand, Capacity}
Number of trucks = 243
Average truck delivery = 75 bbls
Therefore Demand = 243 * 75
= 18225 bbls
From Exhibit 1, it is clear that the trucks start unloading at 7 am in the morning to 7 pm in the evening
taking about 12 hours
Total input rate = 18225/12
= 1518.75 bbls/hour
Dry berry input = 30% of input rate = 455.63 bbls/hour
Wet berry input = 70% of input rate = 1063.13 bbls/hour
Processing Capacity = Bottleneck = Drying = 600 bbls/hour
Thus, Flow Rate = Minimum {1063.13, 600}
= 600 bbls/hour
Cycle Time = (1/Flow Rate)
= 1/600 hours/bbl
The demand for wet berries is 70% of total input 18225 = 12758
Flow Rate = 600 bbls/hour
Thus the Flow Rate for 12758 bbls = (12758/600)
= 21.26 hours
This means that on a peak day, it would take close to 21.26 hours to process the berries starting at 7 am
in the morning up to 4.16 am in the morning the next day.
6. How bad is the truck delay at the loading dock during peak season? (3 points)
Answer
Considering the data available in Exhibit 1 for September 23, 1995 which is a day in the peak season, the
following are calculations for unloading of berries and waiting for trucks:
Inventory build-up rate = Percentage of wet berry input – Bottleneck processing capacity
= 1063.12 – 600
= 463.13 bbls/hour
Capacity of wet bins = (8 * 250) + (3 * 400)
= 3200 bbls
The time taken by the trucks to unload the berries into the bins continuously = (3200/463.13)
= 6.91 hours
This corresponds to 1:55 pm in the afternoon. Thus, the trucks unload berries into wet bins continuously
from 7 am to 1.55 pm in the afternoon. The trucks start waiting after 1.55 pm.
Since the inventory is (463.13 * 12) 5557.56 bbls for the day, at 7 pm 3200 bbls are emptied into the bins
and the remaining 2357.56 bbls are still in the trucks.
The remaining 2357.56 bbls in the truck takes close to (2357.56/600) 3.93 hours to be emptied into the
wet bins. This is approximately around 10:56 pm in the night. Thus, there are no trucks waiting at 10:56
pm in the night.
Thus, the waiting time for the trucks = (12+3.93) – 6.91
= 15.93 – 6.91
= 9.02 hours
7. What recommendations, both short and long term, would you make to Mr. Schaeffer to overcome
the problems identified in (1)? (15 points)
Answer
1. If one dryer is installed and simultaneously converting 8 dry bins to wet bins (Total wet bins = 19 bins),
it helps reduce the truck waiting time to an extent, and this in turn gives a significant difference when
compared to 1995 model in the short run.
2. If two dryers are installed and simultaneously converted 5 dry bins to wet bins (Total wet bins = 16
bins), a notable change in the truck wait time is observed and the savings are remarkable. Hence, this
would be a better solution in the long run.
3. The grading of berries incorrectly incurred a sizeable amount of loss. This is overcome by installation of
a light meter system.
Without Dryer
Processing Capacity of three dryers = (3 * 200) = 600 bbls/hour
Since the demand on 23rd September is 12758 bbls, the receiving plant operates for 21.26 hours which is
from 7 am in the morning to 4.16 am the next day morning.
Addition of one dryer
Processing Capacity for four dryers = (4 * 200) = 800 bbls/hour
Assuming the same demand as of 23rd September, the receiving plant operates for 15.95 hours which is
from 7 am in the morning to 10.57 pm in the night.
Addition of two dryers
Processing Capacity for five dryers = (5 * 200) = 1000 bbls/hour
Assuming the same demand as of 23rd September, the receiving plant operates for 12.76 hours which is
from 7 am in the morning to 7.46 pm in the night.
1.Hourly cost of labor
Length of the peak season = 16 weeks
Number of working days per week = 7
Average salary for an employee (including both seasonal and non-seasonal rates), i.e., (8+13)/2
= $10.5
Average number of employees = 35 (assuming both less and more supply of berry days)
The total hourly cost of labor for the 16 weeks = (16 * 7 * 10.5 * 45)
= $41,160
This is the hourly cost of labor for two shifts 7 am to 3 pm and 3 pm to 11 pm.
Since there is a need of 9 employees to work overtime after 11 pm, the hourly cost of labor for 9
employees after 11 pm = $8,232
Installing one dryer reduces the operation of the receiving plant from 4.16 am to 10.57 pm, that is, 5.32
hours.
Installing two dryers reduces the operation of the receiving plant from 10.57 pm am to 7.46 pm, that is,
3.18 hours.
Savings due to the reduced hours = (5.32 * 8,232) + (3.18 * 41,160)
= 43,794.24 + 130,888.8
= $174,683.04
Cost of installing two dryers = $60,000 * 2 = $120,000
Actual savings = $174,683.04 - $120,000
= $54,683.04
2.Conversion of Bins
Addition of 1 dryer
Processing Capacity = (4 * 200) = 800 bbls/hour
Suppose 8 bins are converted then the capacity of bins to process dry berries and wet berries is as follows:
Wet Berries = (16 * 250) + (3 * 400)
= 5200 bbls
Dry Berries = (8 * 250)
= 2000 bbls
Time taken for 800 barrels = 1 hour
Time taken for 12758 barrels = 15.95 hours
Thus, flow rate = (12758/15.95)
= 799.87 bbls/hour
Capacity of wet bins = 5200 bbls
Time taken by the trucks to empty the berries into wet bins = 5200/799.87
= 6.5 hours
Thus, the trucks start waiting from 1:30 pm in the afternoon.
Processing Capacity = 800 bbls
Inventory build-up rate = 799.87 – 800
= -0.13 bbl/hour
Total Inventory build-up = (799.87 * 4) + (-0.13 * 12)
= 3197.92 bbls (which is less than the capacity)
Waiting time for trucks = (3197.92/799.97) + 6.5
= 10.49 hours
Thus, the waiting time for trucks increases by 10 hours and 30 minutes
Addition of 2 dryers
Processing Capacity = (5 * 200) = 1000 bbls/hour
Suppose 5 bins are converted then the capacity of bins to process dry berries and wet berries is as follows:
Wet Berries = (5 * 250) + (3 * 400) + (8*250)
= 4450 bbls
Dry Berries = (11 * 250)
= 2750 bbls
Time taken for 1000 barrels = 1 hour
Time taken for 12758 barrels = 12.76 hours
Thus, flow rate = (12758/12.76)
= 999.84 bbls/hour
Capacity of wet bins = 4450 bbls
Time taken by the trucks to empty the berries into wet bins = 4450/999.84
= 4.45 hours
Thus, the trucks start waiting from 11:27 am in the afternoon.
Processing Capacity = 1000 bbls
Inventory build-up rate = 999.84 – 1000
= -0.16 bbl/hour
Total Inventory build-up = (999.84 * 4) + (-0.16 * 9)
= 3997.92 bbls (which is less than the capacity)
Waiting time for trucks = (3997.92/999.84) + 4.45
= 8.44 hours
Thus, the waiting time for trucks decreases by 8 hours and 26 minutes
3.Installation of Light Meter System
Cost of installing a single Light Meter System = $40,000
Assuming the salary paid to an employee to be x and considering the incoming time of trucks for a day
to be 12.76 hours, then
Daily wages of an employee = (12.76 * x)
Weekly wages of the employee = (12.76 * 7 * x)
= 89.32x
Yearly salary of the employee = 52 weeks * 89.32x
Assuming the hourly wage of the employee as $10, then
Yearly salary of the employee = $46,446.40
Thus, the total investment to install the light meter system = $40,000 + $46,446.40
= $86,446.40
In 1995, the $1.50 premium was paid on about 450,000 bbls due to incorrect grading of berries. When
these berries were later used, it was found that only half of them were grade 3 berries which led to a
notable loss of price paid.
Total premium paid = $1.50 * 450,000
= $675,000
Loss incurred = $337,500
Hence the total savings = $337,500 - $86,446.40
= $251,053.60