Transcript Facility Location

Facility Location
Relevance of Facility Location Decisions.
Types & Causes of Facility Location.
General Process for Facility Location.
Trends and Future Strategies.
Methods for Facility Location Selection.
Location Case Studies
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Case 1: Ikea has not open a center in Valencia.
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Case 2: After a fire at its painting facilities in Stutgart,
Schefenacker AG, the biggest rear view mirror manufacturer in
the world, decides to open a new facility in Mosonmagyorovar
(Hungary). It will be the thrid painting facility of this type after
(USA and South Korea).
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Case 3: Grupo F Segura, following the requirements of their
clients (mainly VW group) opens a factory at Hungary.
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Case 4: Ford Motor Company is to decide where to assemble the
next generation of Ford Focus and Ford Fiesta.
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Case 5: Zara UK is opening a new store in Canary Wharf
Importance of Facility Location
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Facility Location decisions are part of the company’s strategy. Infrequent
but expensive.
Reasons for the importance:
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Facility Location requires large investment that can not be recovered.
Facility Location decisions affect the competitive capacity of the company.
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The facility location decisions affect not only costs but the company’s
income:
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All areas of the company are affected by Facility Location: Operations, but also
Business Development, Human Resources, Finance, etc.
For a service business, market proximity is critical to determine the capacity to
attract customers.
For a manufacturing business, facility location affects product delivery time and
level of customer service, which affects sales.
Regarding costs, facility location affects a great variety of them:
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Land costs.
Labor costs.
Raw materials.
Transportation and distribution
Topics
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Importance of Facility Location.
Causes & Types of Facility Location.
Issues at Location
General Process for Facility Location.
Trends and Future Strategies.
Locating Service Facilities
Methods for Facility Location Selection.
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Centroid Methods
Factors Rating Analysis.
Economic Analysis.
Transportation (Mathematical Programming Methods).
Set Covering.
Causes that originate Location decision problems
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An expanding market.
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Introduction of new products or services.
A contracting demand, or changes in the location of the demand.
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It means the creation of a new modern plant somewhere else.
The pressure of the competence.
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Example: Extraction companies.
Obsolescence of a manufacturing facility due to the appearance of
new technologies.
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It may require the shut down and/or relocation of operations.
The exhaustion of raw materials in a certain area.
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It will require the addition of more capacity at a certain geographic
point, either in an existent facility or in a new one.
To increase the level of service, it can force the company to increase
capacity of certain plants or relocate some of them.
Change in other resources, like labor conditions or subcontracted
components, or change in the political or economic environment in a
certain region.
Mergers and acquisitions.
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Some facilities may appear as redundants, or bad located with respect
to others.
Location Alternatives
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Expansion of an existent facility.
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Only possible if exists enough space.
Attractive alternative when the current facility location is good
enough for the company.
Lower costs than other options
Start a new facility in a new area.
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Sometimes is a more advantageous option than the previous one
(if there are problems related to lose of focus on the company’s
objectives).
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Shut down of a facility and (or not) starting of a new one
somewhere else.
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Moving production from one plant to other.
Topics
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Importance of Facility Location.
Causes & Types of Facility Location.
Issues at Location
General Process for Facility Location.
Trends and Future Strategies.
Locating Service Facilities
Methods for Facility Location Selection.
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Centroid Methods
Factors Rating Analysis.
Economic Analysis.
Transportation (Mathematical Programming Methods).
Set Covering.
Issues in Facility Location
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Proximity to Customers
Business Climate
Total Costs
Infraestructure
Quality of Labor
Suppliers
Other Facilities
Political Risks
Government Barriers
Trading Blocks
Environmental Regulation
Host Community
Competitive Advantage
Plant Location Methods
If the Boss likes Bakersfield, I like Bakersfield
Topics
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Importance of Facility Location.
Causes & Types of Facility Location.
Issues at Location
General Process for Facility Location.
Trends and Future Strategies.
Locating Service Facilities
Methods for Facility Location Selection.
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Centroid Methods
Factors Rating Analysis.
Economic Analysis.
Transportation (Mathematical Programming Methods).
Set Covering.
Competitive STRATEGY
INTERNAL CONSTRAINTS
Capital, growth strategy,
existing network
PRODUCTION TECHNOLOGIES
Cost, Scale/Scope impact, support
required, flexibility
COMPETITIVE
ENVIRONMENT
GLOBAL COMPETITION
PHASE I
Supply Chain
Strategy
PHASE II
Regional Facility
Configuration
REGIONAL DEMAND
Size, growth, homogeneity,
local specifications
POLITICAL, EXCHANGE
RATE AND DEMAND RISK
PHASE III
Desirable Sites
PRODUCTION METHODS
Skill needs, response time
FACTOR COSTS
Labor, materials, site specific
TARIFFS AND TAX
INCENTIVES
PHASE IV
Location Choices
AVAILABLE
INFRASTRUCTURE
LOGISTICS COSTS
Transport, inventory, coordination
Levels of Decisions.
Market Region
Market Potential
Market Share
Operating Cost
Subregion
Transport Cost (RM)
Taxes
Raw material costs
Labor Cost and Availability
Community
Access to market/materials
Material Cost
Labor Cost and Availability
Taxes
Availability of public services
Availabilty of sites
Community amenities
Sites
Access to transport Network
Site Characterics
Taxes
Availability of public services
Land and acquisition costs
Construction Costs
General Process for Facility Location
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Creation of a multifunctional team to perform the study.
Preliminary analysis.
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Study of the company’s strategies and the policies of the company to
translate them into Facility Location requirements.
Due to the big quantity of factors affecting Facility Location, the company
should determine which is the criteria to evaluate the different alternatives
(transportation needs, land, supplies, labor, infrastructures, services,
environmental conditions…).
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Search of Location Alternatives.
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Establishment of a group of location candidates.
Evaluation of Alternatives (detailed analysis).
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The multifunctional team must distinguish between: Dominant factors
(essential); Secondary factors (desirable).
Information gathering from each location to be measured against each of
the factors considered.
Selection of Facility Location.
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Through qualitative and quantitative analysis, the different alternatives will
be compared against each other, to determine several valid locations.
Objective: Look for several acceptable locations, to let senior management
to decide taking into account subjective factors.
Topics
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Importance of Facility Location.
Causes & Types of Facility Location.
Issues at Location
General Process for Facility Location.
Trends and Future Strategies.
Locating Service Facilities
Methods for Facility Location Selection.
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Centroid Methods
Factors Rating Analysis.
Economic Analysis.
Transportation (Mathematical Programming Methods).
Set Covering.
Trends & Future Strategies
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Most of the Facility Location factors vary with time:
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The accelerated changes in the economic environment are
impacting the frequency of Facility Location decisions.
Changes in the economic environment:
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International level competition among companies.
Location in countries different than the origin of the company are a
common situation for big companies.
Appearance of new markets and unification of others.
Increase of competition pressure.
Logistics factors are more important and complex.
Companies are reviewing their facility locations in order not to
loose competitiveness.
Trends & Future Strategies
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Changes in the economic environment:
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Industry processes automation.
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Labor costs become less important: countries with lower labor
costs become less attractive.
Labor qualification, flexibility and mobility become more
important factors.
However, labor costs are still a main factor in some industries
and in certain manufacturing processes of others: Relocation to
Mexico, Taiwan, Singapore, etc.
Trends & Future Strategies
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Changes in the economic environment:
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Transportation and IT development.
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Helps in the internationalization of the operations: higher
geographical diversity in location decisions.
Tendency to localize close to the markets: emphasis in
customer service, direct customer contact, fast development of
new products, fast delivery…
Due to flexible technologies, companies have the possibility of
starting up more plants at a smaller size.
J.I.T. Systems.
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Some industries are forcing their suppliers and customers to
locate their facilities in a close area to reduce transportation
costs and supply at a higher frequency.
Topics
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Importance of Facility Location.
Causes & Types of Facility Location.
Issues at Location
General Process for Facility Location.
Trends and Future Strategies.
Locating Service Facilities
Methods for Facility Location Selection.
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Centroid Methods
Factors Rating Analysis.
Economic Analysis.
Transportation (Mathematical Programming Methods).
Set Covering.
Locating service facilities
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Because of the variety of service firms and the relatively low
cost of establishing a service facility compared to one for
manufacturing, new service facilities are far more common
than new factories and warehouses.
Services typically have multiple sites to maintain close contact
with customers. The location decision is closely tied to the
market selection decision.
Market affects the number of sites to be built and the size and
characteristics of the sites.
Whereas manufacturing location decisions are often made by
minimizing costs, many service location decision techniques
maximize the profit potential of various sites.
Cost vs Response TIme
Hi
Local FG
Mix
Regional FG
Local WIP
Cost
Central FG
Central WIP
Central Raw Material and Custom production
Custom production with raw material at suppliers
Low
Low
Response Time
Hi
Response Time 1 week-> 1 Distribution Center
Clientes
Centro
distribución
Response Time 5 days-> 2 Distribution Center
Clientes
Centro
distribución
Response Time 3 days-> 5 Distribution Center
Clientes
Centro
distribución
Response Time 1 day-> 13 Distribution Center
Clientes
Centro
distribución
Same Day Response --> 26 Distribution Centers
Customer
DC
Response
Time
Response time vs. Number of facilities
Number of Facilities
Cost vs Number of Facilities
Total Costs
Cost of Operations
Percent Service
Level Within
Promised Time
Facilities
Inventory
Transportation
Labor
Number of Facilities
Topics
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Importance of Facility Location.
Causes & Types of Facility Location.
Issues at Location
General Process for Facility Location.
Trends and Future Strategies.
Locating Service Facilities
Methods for Facility Location Selection.
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Centroid Methods
Factors Rating Analysis.
Economic Analysis.
Transportation (Mathematical Programming Methods).
Set Covering.
Methods of Facility Location Selection
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Centroid Methods
Factors Rating Analysis.
Economic Analysis.
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Income independent upon location.
Income dependent upon location.
Transportation (Mathematical Programming Methods).
Set Covering.
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No limitation of facilities.
Limitation of facilities.
Centroid Method
N/S
150
120
Transport cost are related to volume
1.000
90
1.000
2.000
60
30
2.000
E/O
30
60
Origen arbitrario
Cx =
d V
V
ix
120
150
i
i
Cy =
90
d V
V
iy
i
i
Cx , Cy = Gravity Center
dix , diy = coordinates de la ubicación i
Vi
= Volume of goods moved from/to i
Methods of Facility Location Selection
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Centroid Methods
Factors Rating Analysis.
Economic Analysis.
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Income independent upon location.
Income dependent upon location.
Transportation (Mathematical Programming Methods).
Set Covering.
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No limitation of facilities.
Limitation of facilities.
Factor-Rating Method
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Popular because a wide variety of factors can be included in the
analysis
Six steps in the method
 Develop a list of relevant factors called critical success factors
 Assign a weight to each factor
 Develop a scale for each factor
 Score each location for each factor
 Multiply score by weights for each factor for each location
 Recommend the location with the highest point score
Factor-Rating Example
Critical
Success
Factor
Labor
availability
and attitude
People-to
car ratio
Per capita
income
Tax structure
Education
and health
Totals
Weight
Scores
(out of 100)
France Denmark
Weighted Scores
France
Denmark
.25
70
60
.05
50
60
.10
.39
85
75
80
70
(.10)(85) = 8.5 (.10)(80) = 8.0
(.39)(75) = 29.3 (.39)(70) = 27.3
.21
60
70
(.21)(60) = 12.6 (.21)(70) = 14.7
1.00
(.25)(70) = 17.5 (.25)(60) = 15.0
(.05)(50) = 2.5
70.4
(.05)(60) = 3.0
68.0
Table 8.3
Methods of Facility Location Selection
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Centroid Methods
Factors Rating Analysis.
Economic Analysis.
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Income independent upon location.
Income dependent upon location.
Transportation (Mathematical Programming Methods).
Set Covering.
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No limitation of facilities.
Limitation of facilities.
Locational Break-Even Analysis Example
Three locations:
Fixed Variable
City
Cost
Cost
Akron
$30,000
$75
Bowling Green
$60,000
$45
Chicago
$110,000
$25
Selling price = $120
Expected volume = 2,000 units
Total
Cost
$180,000
$150,000
$160,000
Total Cost = Fixed Cost + Variable Cost x Volume
Annual cost
Locational Break-Even Analysis Example
–
$180,000 –
–
$160,000 –
$150,000 –
–
$130,000 –
–
$110,000 –
–
–
$80,000 –
–
$60,000 –
–
–
$30,000 –
–
$10,000 –
|
–
0
Akron
lowest
cost
Chicago
lowest
cost
Bowling Green
lowest cost
|
|
|
|
|
|
500
1,000
1,500
2,000
2,500
3,000
Volume
Methods of Facility Location Selection
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Centroid Methods
Factors Rating Analysis.
Economic Analysis.
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Income independent upon location.
Income dependent upon location.
Transportation (Mathematical Programming Methods).
Set Covering.
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No limitation of facilities.
Limitation of facilities.
Network Optimization Models
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Allocating demand to production facilities
Locating facilities and allocating capacity
Key Costs:
• Fixed facility cost
• Transportation cost
• Production cost
• Inventory cost
• Coordination cost
Which plants to establish? How to configure the network?
Conventional Network
Vendor
DC
Vendor
DC
Materials
DC
Finished
Goods DC
Customer
DC
Customer
Store
Component
Manufacturing
Customer
DC
Plant
Warehouse
Components
DC
Vendor
DC
Final
Assembly
Customer
Store
Customer
Store
Customer
Store
Finished
Goods DC
Customer
DC
Customer
Store
Demand Allocation Model
Which market is served
by which plant?
 Which supply sources
are used by a plant?
xij = Quantity shipped from
plant site i to customer j

n m
Min  cij xij
i 1 j 1
s.t.
n
 xij  D j
i 1
m
 xij  K i
j 1
xij  0
Plant Location with Multiple Sourcing
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yi = 1 if plant is located
at site i, 0 otherwise
xij = Quantity shipped
from plant site i to
customer j
n
n m
i 1
i 1 j 1
Min f i y i    cij xij
s.t.
n
 xij  D j
i 1
n
 xij  K i y i
j 1
m
 yi  k ; y i {0,1}
i 1
Multi-echelon
Regional
Finished
Goods DC
National
Finished
Goods DC
Local DC
Cross-Dock
Store 1
Customer 1
DC
Local DC
Cross-Dock
Customer 2
DC
Regional
Finished
Goods DC
Local DC
Cross-Dock
Store 1
Store 2
Store 2
Store 3
Store 3
Methods of Facility Location Selection
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Centroid Methods
Factors Rating Analysis.
Economic Analysis.
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Income independent upon location.
Income dependent upon location.
Transportation (Mathematical Programming Methods).
Set Covering.
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No limitation of facilities.
Limitation of facilities.
Set Covering Models
Define:
cj
cost of locating facility at site j
aij
xj
=
{
=
{
1
0
1
0
if facility located at site j can cover customer i
Otherwise
if facility located at site j
Otherwise
The set covering problem is to:
The set covering problem is to:
n
Minimize
c
j 1
j
xj
s.t.
n
a
j 1
i, j
x j  1,
x j  0,1 ,
i  1..n
j  1..n
Greedy Heuristic for Set Covering Problem:
Step 1:
Step 2:
Step 3:
Step 4
If cj = 0, for any j = 1, 2, ..., n, set xj = 1 and remove all
constraints in which xj appears with a coefficient of +1.
If cj > 0, for any j = 1, 2, ..., n and xj does not appear with a
+1 coefficient in any of the remaining constraints, set xj = 0.
For each of the remaining variables, determine cj/dj, where
dj is the number of constraints in which xj appears with a +1
coefficient. Select the variable k for which ck/dk is minimum,
set xk = 1 and remove all constraints in which xj appears
with a +1 coefficient. Examine the resulting model.
If there are no more constraints, set all the remaining
variables to 0 and stop. Otherwise go to step 1.
Example:
A rural country administration wants to locate several
medical emergency response units so that it can
respond to calls within the county within eight minutes
of the call. The county is divided into seven population
zones. The distance between the centers of each pair
of zones is known and is given in the matrix below.
Imagine that the one that has to make the decision
does not want to place a emergency unit on B or D
Example:
[dij]=
1
2
3
4
5
6
7
1
0
8
50
9
50
30
8
2
4
0
13
11
8
5
5
3
12
15
0
8
4
7
9
4
6
60
8
0
10
9
7
5
15
7
6
9
0
3
25
6
10
2
5
10
2
0
27
7
8
3
9
3
27
27
0
Example 4:
The response units can be located in the center of population zones 1
through 7 at a cost (in hundreds of thousands of dollars) of 100, 80, 120
110, 90, 90, and 110 respectively. Assuming the average travel speed
during an emergency to be 60 miles per hour, formulate an appropriate
set covering model to determine where the units are to be located and
how the population zones are to be covered and solve the model using
the greedy heuristic.
Solution:
Defining
aij =
{
1
0
if zone i’s center can be reached from center of zone j within 8 minutes
otherwise
and noting that dij > 8, dij <= 8 would yield aij values of 0, 1,
respectively the following [aij] matrix can be set up.
Solution:
Minimize Subject to:
100x1+80x2+120x3+110x4+90x5+90x6+110x7
x1 +
x2 +
x4 +
x1 +
x2 +
x5
x3 +
x4 +
x5
x1
x1
+
,
x2
x2
+
+
x2
x2
+
,
x3
+
x3
x3
+
+
x3
,
x4
x6
x6
+
+
x5
x5
x4
x4
+
+
+
,
x5
+
+
,
x7
x7
=1
=1
=1
x7
=1
=1
x6
x6
x6
=1
,
x7
x7
=1
{0,1}
Greedy Heuristic
Step 1: Since each cj > 0, j = 1, 2, ..., 7,
go to step 2.
Step 2: Since xj appears in each
constraint with a +1 coefficient, go
to step 3.
Greedy Heuristic
Step 3:
c1
100
=
= 33.3
d1
3
c5
90
=
= 22.5
d5
4
c2
80
=
= 16
d2
5
c6
90
=
= 22.5
d6
4
c3
120
=
= 30
d3
5
c7
110
=
= 27.5
d7
4
c4
110
=
= 27.5
d4
4
Greedy Heuristic
Since the minimum ck/dk occurs for k = 2, set x2 = 1 and remove
the first two and the last three constraints. The
resulting model is shown below.
Minimize Subject to:
100x1+120x3+110x4+90x5+90x6+110x7
x3 + x4 + x5 + x6
=1
x3 + x4 +
x7 =1
x1
,
x3 ,
x4 ,
x5 ,
x6 ,
x7 {0,1}
Greedy Heuristic:
Step 4: Since we have two constraints go to step 1.
Step 1: Since c1 > 0, j = 1, 3, 4, ..., 7, go to step 2
Step 2: Since c1 > 0 and x1 does not appear in any of
the constraints with a +1 coefficient, set x1 = 0.
Greedy Heuristic
Step 3:
c3
d3
=
=
=
60
110
=
55
90
=
90
=
90
1
c6
d6
=
2
c5
d5
c7
2
c4
d4
120
=
90
1
d7
=
110
1
=
110
Greedy Heuristic
Since the minimum ck/dk occurs for k = 4, set x4 = 1 and
remove both constraints in the above model since x4
has a +1 coefficient in each. The resulting model is
shown below.
Minimize Subject to:
120x3+90x5+90x6+110x7
x3 , x5 , x6 , x7
=0
Greedy Heuristic:
Step 4:
Since there are no constraints in the above
model, set x3 = x5 = x6 = x7 = 0 and stop.
The solution is x2 = x4 = 1; x1 = x3 = x5 = x6 = x7 =
0. Cost of locating emergency response units to
meet the eight minute response service level is
80 + 110 = 190.