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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 Case 1: Ikea has not open a center in Valencia.

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).

Case 3: Grupo F Segura, following the requirements of their clients (mainly VW group) opens a factory at Hungary.

Case 4: Ford Motor Company is to decide where to assemble the next generation of Ford Focus and Ford Fiesta.

Case 5: Zara UK is opening a new store in Canary Wharf

Importance of Facility Location Facility Location decisions are part of the company’s strategy. Infrequent

but expensive. Reasons for the importance:

Facility Location requires large investment that can not be recovered. Facility Location decisions affect the competitive capacity of the company.

All areas of the company are affected by Facility Location: Operations, but also Business Development, Human Resources, Finance, etc.

The facility location decisions affect not only costs but the company’s income: 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:

Land costs. Labor costs. Raw materials. Transportation and distribution

Topics

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.

Centroid Methods Factors Rating Analysis. Economic Analysis. Transportation (Mathematical Programming Methods). Set Covering.

Causes that originate Location decision problems An expanding market.

It will require the addition of more capacity at a certain geographic point, either in an existent facility or in a new one.

Introduction of new products or services. A contracting demand, or changes in the location of the demand.

It may require the shut down and/or relocation of operations. The exhaustion of raw materials in a certain area.

Example: Extraction companies. Obsolescence of a manufacturing facility due to the appearance of

new technologies. It means the creation of a new modern plant somewhere else.

The pressure of the competence. 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. Some facilities may appear as redundants, or bad located with respect

to others.

Location Alternatives Expansion of an existent facility.

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. Sometimes is a more advantageous option than the previous one

(if there are problems related to lose of focus on the company’s objectives).

Shut down of a facility and (or not) starting of a new one somewhere else.

Moving production from one plant to other.

Topics



Issues in Facility Location 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



PHASE ISupply Chain

Strategy

PHASE IIRegional Facility

Configuration

PHASE IIIDesirable Sites

PHASE IVLocation Choices

Competitive STRATEGY

INTERNAL CONSTRAINTSCapital, growth strategy,existing network

PRODUCTION TECHNOLOGIESCost, Scale/Scope impact, supportrequired, flexibility

COMPETITIVEENVIRONMENT

PRODUCTION METHODSSkill needs, response time

FACTOR COSTSLabor, materials, site specific

GLOBAL COMPETITION

TARIFFS AND TAXINCENTIVES

REGIONAL DEMANDSize, growth, homogeneity,local specifications

POLITICAL, EXCHANGERATE AND DEMAND RISK

AVAILABLEINFRASTRUCTURE

LOGISTICS COSTSTransport, inventory, coordination

Levels of Decisions.Market Region

Subregion

Community

Sites

Market PotentialMarket Share

Operating Cost

Transport Cost (RM)Taxes

Raw material costsLabor Cost and Availability

Access to market/materialsMaterial Cost

Labor Cost and AvailabilityTaxes

Availability of public servicesAvailabilty of sites

Community amenities

Access to transport NetworkSite Characterics

TaxesAvailability of public services

Land and acquisition costsConstruction Costs

General Process for Facility Location Creation of a multifunctional team to perform the study. Preliminary analysis.

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…). The multifunctional team must distinguish between: Dominant factors

(essential); Secondary factors (desirable). Search of Location Alternatives.

Establishment of a group of location candidates. Evaluation of Alternatives (detailed analysis).

Information gathering from each location to be measured against each of the factors considered.

Selection of Facility Location. 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



Trends & Future Strategies Most of the Facility Location factors vary with time:

The accelerated changes in the economic environment are impacting the frequency of Facility Location decisions.

Changes in the economic environment: 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 Changes in the economic environment:

Industry processes automation. 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 Changes in the economic environment:

Transportation and IT development. 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. 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



Locating service facilities 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

Local FG

Mix

Regional FG

Local WIP

Central FG

Central WIP

Central Raw Material and Custom production

Custom production with raw material at suppliers

Cost

Response Time HiLow

Low

Hi

Clientes

Centro distribución

Response Time 1 week-> 1 Distribution CenterResponse Time 1 week-> 1 Distribution Center

Clientes


Response Time 5 days-> 2 Distribution CenterResponse Time 5 days-> 2 Distribution Center

Clientes


Response Time 3 days-> 5 Distribution CenterResponse Time 3 days-> 5 Distribution Center

Clientes


Response Time 1 day-> 13 Distribution CenterResponse Time 1 day-> 13 Distribution Center

Customer

DC

Same Day Response --> 26 Distribution CentersSame Day Response --> 26 Distribution Centers

Response time vs. Number of facilities

Number of Facilities

Res

pons

eT

ime

Cost vs Number of Facilities

Percent Service Percent Service Level Within Level Within

Promised TimePromised Time

TransportationTransportationCos

t of

Ope

rati

ons

Cos

t of

Ope

rati

ons

Number of FacilitiesNumber of Facilities

InventoryInventory

FacilitiesFacilities

Total CostsTotal Costs

LaborLabor

Topics



Methods of Facility Location Selection Centroid Methods Factors Rating Analysis. Economic Analysis.

Income independent upon location. Income dependent upon location.

Transportation (Mathematical Programming Methods). Set Covering.

No limitation of facilities. Limitation of facilities.

Centroid MethodN/S

E/O

Origen arbitrario30 60 90 120 150

30

60

90

120

150

1.000

1.0002.000

2.000

V

V d = C

i

iixx

Cx , Cy = Gravity Centerdix , diy = coordinates de la ubicación iVi = Volume of goods moved from/to i

i

iiyy V

V d = C

Transport cost are related to volume





Factor-Rating Method 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 ScoresSuccess (out of 100) Weighted ScoresFactor Weight France Denmark France Denmark

Labor availability and attitude .25 70 60 (.25)(70) = 17.5 (.25)(60) = 15.0People-to car ratio .05 50 60 (.05)(50) = 2.5 (.05)(60) = 3.0Per capita income .10 85 80 (.10)(85) = 8.5 (.10)(80) = 8.0Tax structure .39 75 70 (.39)(75) = 29.3 (.39)(70) = 27.3Education and health .21 60 70 (.21)(60) = 12.6 (.21)(70) = 14.7

Totals 1.00 70.4 68.0

Table 8.3Table 8.3





Locational Break-Even Analysis Example

Three locations:Three locations:

AkronAkron $30,000$30,000 $75$75 $180,000$180,000

Bowling GreenBowling Green $60,000$60,000 $45$45 $150,000$150,000

ChicagoChicago $110,000$110,000 $25$25 $160,000$160,000

Selling price Selling price = $120= $120

Expected volumeExpected volume = 2,000 = 2,000 unitsunits

FixedFixed VariableVariable TotalTotalCityCity CostCost CostCost CostCost

Total Cost = Fixed Cost + Variable Cost x VolumeTotal Cost = Fixed Cost + Variable Cost x Volume

Locational Break-Even Analysis Example

–$180,000 $180,000 –

–$160,000 $160,000 –$150,000 $150,000 –

–$130,000 $130,000 –

–$110,000 $110,000 –

––

$80,000 $80,000 ––

$60,000 $60,000 –––

$30,000 $30,000 ––

$10,000 $10,000 ––

Ann

ual c

ost

Ann

ual c

ost

| | | | | | |

00 500500 1,0001,000 1,5001,500 2,0002,000 2,5002,500 3,0003,000

VolumeVolume

Akron Akron lowest lowest costcost

Bowling Green Bowling Green lowest costlowest cost

Chicago Chicago lowest lowest costcost

Chicago cost curve

Chicago cost curve

Akron c

ost

Akron c

ost

curv

e

curv

e

Bowling Green

Bowling Green

cost curve

cost curve





Network Optimization Models

Allocating demand to production facilities Locating facilities and allocating capacity

Which plants to establish? How to configure the network?

Key Costs:

• Fixed facility cost• Transportation cost• Production cost• Inventory cost• Coordination cost

Conventional Network

CustomerCustomerStoreStore

MaterialsMaterialsDCDC

ComponentComponentManufacturingManufacturing

VendorVendorDCDC

Final Final AssemblyAssembly

FinishedFinishedGoods DCGoods DC

ComponentsComponentsDCDC

VendorVendorDCDC PlantPlant

WarehouseWarehouse

FinishedFinishedGoods DCGoods DC

CustomerCustomerDCDC







VendorVendorDCDC

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

0

..

1

1

1 1

x

Kx

Dx

ts

xcMin

ij

i

m

jij

j

n

iij

n

i

m

jijij

Plant Location with Multiple Sourcing

yi = 1 if plant is located at site i, 0 otherwise

xij = Quantity shipped from plant site i to customer j

}1,0{;

..

1

1

1

1 11

yky

yKx

Dx

ts

xcyfMin

i

m

ii

ii

n

jij

j

n

iij

n

i

m

jijiji

n

ii

Multi-echelon

RegionalFinished

Goods DC

RegionalFinished

Goods DC

Customer 1DC

Store 1

NationalFinished

Goods DC

Local DCCross-Dock

Local DC Cross-Dock

Local DCCross-Dock

Customer 2DC

Store 1

Store 2

Store 2

Store 3

Store 3





Define:

cj cost of locating facility at site j

aij =

xj =

The set covering problem is to:The set covering problem is to:

Set Covering Models

1 if facility located at site j can cover customer i0 Otherwise

1 if facility located at site j 0 Otherwise

{

{

The set covering problem is to:The set covering problem is to:

1

,1

. .

1, 1..

0,1 , 1..

n

j jj

n

i j jj

j

Minimize c x

s t

a x i n

x j n

Greedy Heuristic for Set Covering Problem:

Step 1: 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.

Step 2: 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.

Step 3: 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.

Step 4 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:

1 2 3 4 5 6 7

1 0 4 12 6 15 10 8

2 8 0 15 60 7 2 3

3 50 13 0 8 6 5 9

4 9 11 8 0 9 10 3

5 50 8 4 10 0 2 27

6 30 5 7 9 3 0 27

7 8 5 9 7 25 27 0

[dij]=

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:

and noting that dij > 8, dij <= 8 would yield aij values of 0, 1, respectively the following [aij] matrix can be set up.

Defining

aij = {1 if zone i’s center can be reached from center of zone j within 8 minutes

0 otherwise

Solution:

100x1+80x2+120x3+110x4+90x5+90x6+110x7

x1 + x2 + x4 + x7 =1

x1 + x2 + x5 + x6 + x7 =1

x3 + x4 + x5 + x6 =1

x3 + x4 + x7 =1

x2 + x3 + x5 + x6 =1x2 + x3 + x5 + x6 =1

x1 + x2 + x4 + x7 =1x1 , x2 , x3 , x4 , x5 , x6 , x7 {0,1}

Minimize Subject to:

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 HeuristicStep 3:

c1d1

1003

= = 33.3

c2d2

805

= = 16

c3d3

1205

= = 30

c4d4

1104

= = 27.5

c5d5

904

= = 22.5

c6d6

904

= = 22.5

c7d7

1104

= = 27.5

Greedy HeuristicSince 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.

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 HeuristicStep 3:

c3

d3120

2= = 60

c4

d4110

2= = 55

c5

d590

1= = 90

c6

d690

1= = 90

c7

d7110

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.


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.

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