operations management
jenny2000000
8_NCCCaseStudy.pptxClass 8 National Cranberry Cooperative
Instructor: Mani Lakshmanan
P300 Introduction to Operations Management
Little’s Law Example – Doughnut Shop
From your daily morning trip to the doughnut shop, you know they have a healthy business, at least financially speaking. As you might want to invest in a franchise, you wonder what amount of revenue they generate.
Over the course of several months; you visit the shop at random times between 6:00AM and 9:00 AM; you observe that the queue averages about 10 customers, and that it takes you about 3 min to get in and out of the shop.
Assume your experience is typical, and each order generates revenue of $10.
Apply Little's Law to estimate the doughnut shop’s revenue for the morning period 6:00AM ~ 9:00 AM.
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“Average” in Little’s Law
| Customer | Arrival | Departure | Departure - Arrival |
| #1 | 5:00 pm | 5:30 pm | 30 mins |
| #2 | 5:02 pm | 5:30 pm | 28 mins |
| #3 | 5:05 pm | 5:42 pm | 27 mins |
| … |
| Time | Number of Customers in the restaurant |
| 5:00 pm | 1 |
| 5:01 pm | 1 |
| 5:02 pm | 2 |
| … |
| Time | Number of Customers leave the restaurant |
| 5:00 pm | 0 |
| 5:01 pm | 0 |
| … | |
| 5:30 pm | 2 |
| … |
Flow Time, T
Inventory, I
Throughput Rate, R
Why we care about I,R,T?
T -> Responsiveness
I -> Inventory Cost
National Cranberry Cooperative
Background & Symptoms
What was the industry trend?
The amount of cranberries to process per year?
The percentage of water-harvested berries?
What are symptoms of NCC RP1’s management problem?
6
Case Assumptions
All the processes (including Destone, Dechaff, and Dry) start from 7am.
On an average “busy” day, there are 18,000 bbls delivered over 12-hour period (from 7am to 7pm).
Wet berries are 70% of all berries.
Holding bins 17-24 are dedicated to wet berries.
Capacity of each of five dumpers is 600 bbl/hr.
There are 20 peak days in one year, where there is truck waiting happened.
Truck Drivers are paid by $18/hr
Why we need these assumptions. Come from the case material.
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Bulk and Bag
Separators
C = 400*3=1200 bbls/hr
Dryers
C =200*3=600 bbls/hr
Destoners
C =1500*3=4500 bbls/hr
Kiwanee Dumpers
C = 600*5=3000 bbls/hr
Trucks in
Queue
Bins 1-16
storage =250*16=4000 bbls
Bins 17-27
storage =250*8+400*3=3200 bbls
Dechaffers
C = 4500, 1500 bbls/hr for dry berries and 3000 bbls/hr for wet berries
Dry berries
18000/12*0.3=450 bbls/hr
Wet berries
18000/12*0.7=1050 bbls/hr
Clarify demand rates
Clarify the difference between Dechaffers and Separators.
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Process Analysis – Capacity
On a busy day, what is RP#1’s current maximum throughput rate?
Compare demand rate and capacity rate for wet and dry berries, respectively.
Bulk and Bag
Separators
C = 400*3=1200 bbls/hr
Dryers
C =200*3=600 bbls/hr
Destoners
C =1500*3=4500 bbls/hr
Kiwanee Dumpers
C = 600*5=3000 bbls/hr
Trucks in
Queue
Bins 1-16
storage =250*16=4000 bbls
Bins 17-27
storage =250*8+400*3=3200 bbls
Dechaffers
C = 4500, 1500 bbls/hr for dry berries and 3000 bbls/hr for wet berries
Dry berries
18000/12*0.3=450 bbls/hr
Wet berries
18000/12*0.7=1050 bbls/hr
Clarify demand rates
Clarify the difference between Dechaffers and Separators.
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Bulk and Bag
Separators
C = 400*3=1200 bbls/hr
Dryers
C =200*3=600 bbls/hr
Destoners
C =1500*3=4500 bbls/hr
Kiwanee Dumpers
C = 600*5=3000 bbls/hr
Trucks in
Queue
Bins 1-16
storage =250*16=4000 bbls
Bins 17-27
storage =250*8+400*3=3200 bbls
Dechaffers
C = 3000 bbls/hr
Dry berries
18000/12*0.3=450 bbls/hr
Wet berries
18000/12*0.7=1050 bbls/hr
Dechaffers
C = 1500 bbls/hr
Clarify demand rates
Clarify the difference between Dechaffers and Separators.
11
Bulk and Bag
Separators
C = 1200 bbls/hr
Destoners
C =4500 bbls/hr
Kiwanee Dumpers
C = 3000 bbls/hr
Trucks in
Queue
Bins 1-16
storage =4000 bbls
Dry Berries:
Dry Berries Bottleneck:
Dryers
C =600 bbls/hr
Bins 17-27
storage =3200 bbls/hr
Dechaffers
C = 3000 bbls/hr
Dechaffers
C = 1500 bbls/hr
Dry berries
18000/12*0.3=450 bbls/hr
Bulk and Bag
Separators
C = 1200 bbls/hr
Dryers
C =600 bbls/hr
Kiwanee Dumpers
C = 3000 bbls/hr
Trucks in
Queue
Bins 17-27
storage =3200 bbls
Wet Berries:
Wet Berries Bottleneck:
Destoners
C =4500 bbls/hr
Bins 1-16
storage =4000 bbls
Dechaffers
C = 3000 bbls/hr
Dechaffers
C = 1500 bbls/hr
Wet berries
18000/12*0.7=1050 bbls/hr
Bulk and Bag
Separators
C = 1200 bbls/hr
Dryers
C =600 bbls/hr
Destoners
C =4500 bbls/hr
Kiwanee Dumpers
C = 3000 bbls/hr
Trucks in
Queue
Bins 1-16
storage =4000 bbls
Bins 17-27
storage =3200 bbls
Combine:
Dry berries
18000/12*0.3=450 bbls/hr
BN: 1200 bbls/hr
Wet berries
18000/12*0.7=1050 bbls/hr
BN: 600 bbls/hr
Dechaffers
C = 3000 bbls/hr
Dechaffers
C = 1500 bbls/hr
>1050 bbls/hr
>1050 bbls/hr
Clarify demand rates
Clarify the difference between Dechaffers and Separators.
14
Inventory Buildup Diagram
7am
10am
1pm
4pm
7pm
10pm
1am
4am
7am
1000
2000
3000
4000
5000
Inventory [bbl.]
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Inventory Buildup Diagram
7am
10am
1pm
4pm
7pm
10pm
1am
4am
7am
1000
2000
3000
4000
5000
Inventory [bbl.]
Total
3200
2:07pm
10:40pm
5400
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Consequently, we need to figure out the inventory buildup diagram for the wet berries. Now let me roughly go through it once again. To make an inventory buildup diagram is not a very tough thing, as long as you remember two steps. First, what is the buildup rate and how long will the buildup continue? Second, what is reducing rate and how long will it take to reach the lowest level? In this case, the buildup rate is 450/hr, the buildup will continue till 7pm, reaching the highest level 5400. This is the end of first step. Now second step. What is the reducing rate? 600/hr. When will all of inventory disappear? 9 hours later, at 4am. The end of second second. And at the same time, the diagram is finished. The only thing you need to notice here is that the inventory will stay in two different places. First in bins, when it is full, then on trucks. So, you also need to figure out the time window that trucks wait.
Now, with this analysis, let us recall their management problems. What can you conclude? Are those symptoms expectable? What are the cause to them? Why do we observe long overtime and long truck waiting time? The wet berries’ inventory. The unbalance between wet berries demand rate and capacity rate. Then what could be the solution to them?
Inventory Buildup Diagram
7am
10am
1pm
4pm
7pm
10pm
1am
4am
7am
1000
2000
3000
4000
5000
Inventory [bbl.]
Trucks
Bins
3200
2:07pm
10:40pm
2200
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Now, with this analysis, let us revisit those symptoms. What can you conclude? Are they expectable? What are the cause to them? The unbalance between demand and capacity rates, especially for those wet berries. Ok, next class, we are going to think about how to solve their management problems.
Capital Investments considered by NCC
(Install the 5th Kiwanee Dumper)
Convert dry berry holding bins into wet/dry berry holding bins
Install a few new dryers
Install a light meter system
Cost/Benefit Analysis
Install the 5th Kiwanee Dumper
Cost
$200k
Benefit
$0
Cost/Benefit Analysis
Convert dry berry holding bins into wet/dry berry holding bins
Cost
$10k each
Benefit?
Saving by eliminate the truck waiting completely
How many dry bins do we need to convert to wet bins?
Inventory in truck is total 2200 bbls. Each bin holds 250 bbls. Hence, 2200/250 = 8.8 = 9 bins.
The total cost is 9 $10k = $90K
Cost/Benefit Analysis
Convert dry berry holding bins into wet/dry berry holding bins
Benefit per day:
Average truck waiting time
Saving per truck per hour = $18
Number of trucks per hour = 1500*0.7/75=14
The length of time when a truck arrives needs to wait = 7pm-2:07pm= 4.89hrs
Total saving per day = Avg. waiting time *18*14*4.89
Avg. Flow time = Avg. inv. / Avg. throughput rate
M1:
Ask methods, summarize the logic.
There are multiple ways to calculate the number.
Methodology discussion! Explain to the class.
One of the three make sense, I’m very happy!
21
Cost/Benefit Analysis
Avg. Flow time = Avg. inv. / Avg. throughput rate
M1:
Ask methods, summarize the logic.
There are multiple ways to calculate the number.
Methodology discussion! Explain to the class.
One of the three make sense, I’m very happy!
22
Cost/Benefit Analysis
Convert dry berry holding bins into wet/dry berry holding bins
Benefit per day:
Average truck waiting time = 11/6
Saving per truck per hour = $18
Number of trucks per hour = 1500*0.7/75=14
The length of time when a truck arrives needs to wait = 7pm-2:07pm= 4.89hrs
Total saving per day = Avg. waiting time *18*14*4.89
= 11/6 * 18 *14* 4.89
= $2260
Saving per year = 2260 * 20 = $45.2k
Avg. Flow time = Avg. inv. / Avg. throughput rate
M1:
Ask methods, summarize the logic.
There are multiple ways to calculate the number.
Methodology discussion! Explain to the class.
One of the three make sense, I’m very happy!
23
Cost/Benefit Analysis
Convert dry berry holding bins into wet/dry berry holding bins
Benefit per day:
Average truck waiting time = 11/6 hrs
Average truck waiting time = (10:40pm-7pm)/2 = 11/6 hrs
Avg. Flow time = Avg. inv. / Avg. throughput rate
M2:
Cost/Benefit Analysis
Convert dry berry holding bins into wet/dry berry holding bins
Benefit per day:
Total waiting time (bbls·hr) = area of small triangle
= 0.5 2200 bbls (10:40pm – 2:07pm) hrs = 9416 bbls·hr
Total waiting time (tr·hr)= 9416/75=125.54 tr·hr
Total saving per day = 125.54 *18= $2260
Benefit per year:
2260*20 = $ 45.2k
M3:
Capital Investments considered by NCC
(Install the 5th Kiwanee Dumper)
Convert dry berry holding bins into wet/dry berry holding bins
Install a few new dryers
Install a light meter system
National Cranberry Takeaways
Process capacity analysis for mixed products
Separate & Combine
Adding buffer size may reduce the delay
Use of inventory build-up diagram to estimate the costs of system delay
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At the end, I can go through the homework to fill all the remaining time.
Bulk and Bag
Separators
C = 1200
Dryers
C =800
Destoners
C =4500
Kiwanee Dumpers
C = 3000
Trucks in
Queue
Bins 1-16
storage =4000
Bins 17-27
storage =3200
Dechaffers
C = 4500
Dry berries
450 bbl/hr
Wet berries
1050 bbl/hr
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Inventory Buildup Diagram
7am
10am
1pm
4pm
7pm
10pm
1am
4am
7am
1000
2000
3000
4000
5000
Inventory [bbl.]
Bins for Dry
Bins for Wet
3200
10:45pm
8:30pm
600
5.25 hr
1.5hr
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Cost/Benefit Analysis
Assumption I: There are 20 peak days in one year, where there is truck waiting happened.
Assumption II: Truck drivers are paid $18/hr.
Install the 5th Kiwanee Dumper
Cost: $200k
Benefit: $0
Convert dry berry holding bins into wet/dry berry holding bins
Cost: $10000 each
Convert 9 bins: $90K
Benefit:
Each peak day: $2260
Every year: $45.2K
Two new dryers
Cost: $60K each
Benefit: (only one dryer)
Truck waiting: $45.2K
Overtime: 3.75 hours
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