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VENDOR MANAGED INVENTORY
Anton Kleywegt
School of Industrial and Systems Engineering
Georgia Institute of Technology
Atlanta, GA 30332-0205
[email protected]
(404) 894-4323
TLI Transportation/Distribution/Logistics Short Course
Georgia Institute of Technology
April 4, 2001
Here’s what we’ll talk about...
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



What is “Vendor Managed Inventory” (VMI)?
Why are we interested in VMI?
What does one need to make VMI work?
Case study: Praxair Supply Management
Lessons learned
Conventional Inventory
Management


Customer

monitors inventory levels

places orders
Vendor

manufactures/purchases product

assembles order

loads vehicles

routes vehicles

makes deliveries
Problems with Conventional
Inventory Management

Large variation in demands
on production and
transportation facilities

workload balancing

utilization of resources

unnecessary transportation
costs

urgent vs nonurgent orders

setting priorities
MICHIGAN
Detroit
LAKE ERIE
Cleveland
OHIO
Conventional Inventory Management -- Day 1
MICHIGAN
Detroit
LAKE ERIE
Cleveland
OHIO
Conventional Inventory Management -- Day 2
MICHIGAN
Detroit
LAKE ERIE
Cleveland
OHIO
Vendor Managed Inventory

Customer


trusts the vendor to manage
the inventory
Vendor

monitors customers’ inventory




customers call/fax/e-mail
remote telemetry units
set levels to trigger call-in
controls inventory
replenishment & decides



when to deliver
how much to deliver
how to deliver
Vendor Managed Inventory -- Day 1
MICHIGAN
Detroit
LAKE ERIE
Cleveland
OHIO
Vendor Managed Inventory -- Day 2
MICHIGAN
Detroit
LAKE ERIE
Cleveland
OHIO
Advantages of VMI

Customer



less resources for inventory
management
assurance that product will be available
when required
Vendor



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more freedom in when & how to
manufacture product and make deliveries
more uniform utilization of resources
better coordination of inventory levels at
different customers
better coordination of deliveries to
decrease transportation cost
Applications of VMI


Chemical Industry

air products distribution

carbon black distribution
Petrochemical industry


Automotive Industry


gas stations
parts distribution
Consumer Products

Department and grocery stores
Praxair’s Business

Not an airline!

Air products

“harvest the sky”

produce nitrogen, oxygen, argon, hydrogen, helium,
etc.
Praxair’s Business
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Plants worldwide

44 countries

USA 70 plants

South America 20 plants
Product classes

packaged products

bulk products

lease manufacturing
equipment
Distribution

1/3 of total cost attributed to
distribution
Praxair’s Business
Bulk products


Distribution

750 tanker trucks

100 rail cars

1,100 drivers

drive 80 million miles per year
Customers



45,000 deliveries/month to 10,000 customers
Variation

4 deliveries/customer/day to

1 delivery/customer/2 months
Routing varies from day to day
Praxair’s Business
Production Facility A
Praxair’s Business
Production Facility B
Praxair’s Business
D e liv e r ie s P e r W e e k f o r P la n t A C u s t o m e r s
n u m b e r o f d e liv e r ie s
6
5
4
3
2
1
0
1
6
11
16
21
26
c u s to m e r
31
36
41
46
Praxair’s Business
D e liv e r ie s P e r W e e k f o r P la n t B C u s t o m e r s
4 .5
n u m b e r o f d e liv e r ie s
4
3 .5
3
2 .5
2
1 .5
1
0 .5
0
1
6
11
16
21
26
31
36
41
46
cu s to m e r
51
56
61
66
71
76
81
86
Praxair’s Business
T a n k S iz e s f o r P la n t A
90000
80000
t a n k s iz e
70000
60000
50000
40000
30000
20000
10000
0
1
6
11
16
21
26
c u s to m e r
31
36
41
46
Praxair’s Business
T a n k S iz e s f o r P la n t B
3000000
ta n k s iz e
2500000
2000000
1500000
1000000
500000
0
1
6
11
16
21
26
31
36
41
46
51
c u s to m e r
56
61
66
71
76
81
86
VMI Implementation at Praxair


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Convince management and employees of new
methods of doing business
Convince customers to trust vendor to do inventory
management
Pressure on vendor to perform - Trust easily shaken
Praxair currently manages 80% of bulk customers’
inventories
Demonstrate benefits
VMI Implementation at Praxair

Praxair receives inventory level data via




Forecast customer demands based on

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telephone calls: 1,000 per day
fax: 500 per day
remote telemetry units: 5,000 per day
historical data
customer production schedules
customer exceptional use events
Logistics planners use decision support tools to plan





whom to deliver to
when to deliver
how much to deliver
how to combine deliveries into routes
how to combine routes into driver schedules
Benefits of VMI at Praxair
10
5
Dec
Nov
Oct
Sept
Aug
July
June
May
Apr
after 2 yrs
Mar
0
before VMI
Feb

Before VMI, 96% of
stockouts due to customers
calling when tank was
already empty or nearly
empty
VMI reduced customer
stockouts
Jan

What’s needed to make VMI work

Information management is crucial to the success of VMI




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inventory level data
historical usage data
planned usage schedules
planned and unplanned exceptional usage
Accurate and timely forecasts of future demand
Convince management that VMI will be beneficial, and that it
can be implemented successfully
Convince customers that VMI will be to their benefit
Make good replenishment decisions - decision support
Inventory Routing Problem

Products

Drivers and Vehicles

Costs

Transportation cost

Revenue earned

Shortage cost


Customers
Plants
Inventory holding cost
0
0,0
Vehicles

0
1,0
0
2,0
V1(x1,0)
V1(x1,0)
V1(x1,0)
0
0,1
V2(x2,0
)
0
0,2
V3(x3,0)
0,3
0
0
0
1,1
1,2
1,3
0
2,1
V2(x2,0
)
0
2,2
V3(x3,0)
Objective

0
Choose a distribution policy that maximizes the expected total
discounted value (rewards minus costs) over a long horizon
0
2,3
Inventory Routing Problem
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Decision making: decide on a regular (daily) basis
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
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whom to deliver to
when to deliver
how much to deliver
how to combine deliveries into routes
how to combine routes into driver schedules
Important factors to take into account

Likelihood of customer stocking out

Consequences if customer stocks out

Impact of today’s decisions on future situation

Benefits of coordinating deliveries to close customers
Georgia Tech researchers have developed methods to solve
the inventory routing problem
INVENTORY ROUTING
PROBLEM
Anton Kleywegt
Vijay Nori
Martin Savelsbergh
These papers can be obtained from
http://tli.isye.gatech.edu/reports.html
Vendor Managed Inventory