facility location cob 300c – fall 2002. facility location 4 facility location is the placement of...
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Facility Location
COB 300C – Fall 2002
Facility Location Facility Location is the placement of facility with respect to
customers, suppliers and other interacting facilities. It should consider:– Operating costs
– Customer convenience
– Transportation costs
– Access to key related services
such as banking and
educational opportunities
– Strategic factors
Location as a Strategic DecisionLocation as a Strategic Decision
1. Long-term commitment
2. Linked to customer base
3. Regional facility supplies specific area
4. Product facility supplies globally
5. Combination of regional and product facilities
Regional or Global
Factors Affecting theLocation Decision
Strategic nature of decision
Quantitative factors Government incentives Qualitative factors
Including theQualitative Factors
Integrate qualitative factors
– Determine which factors are relevant to the problem
– Weigh each factor
– Rate each site for each factor
Examples of Indianapolis and Lexington (Slide 1 of 2)
Indianapolis Lexington Weight Raw Score Raw Score
Recreational activities 20 8 7University research facilities 40 8 8Union activities 40 4 7Banking services 80 7 6Available labor pool 60 7 5
Examples of Indianapolis and Lexington (Slide 2 of 2)
Indianapolis Lexington
Weighted score Weighted score
Recreational activities 160 140 University research facilities 320 320Union activities 160 280Banking services 560 480Available labor pool 420 300
Total 1,620 1,520
Analyzing Spatial RelationshipsAnalyzing Spatial Relationships
Load-Distance Method measures proximity to customers, suppliers, interacting facilities
Transportation Problem relates to the cost of transporting materials to and from multiple facilities
Distance from Facilityto Customer
Health Care UnitLocation Problem
Locating a Health Care Center Using the “Load-Distance Method” (Slide 1 of 3)
Population coordinates
Code ai xi yi (ai )(xi) (ai)(yi)
10111 30,000 3 2 90,000 60,00010112 25,000 2 4 50,000 100,00010113 11,000 1.5 5.5 16,500 60,50010114 8,000 3 7 24,000 56,00010115 18,000 3.5 5 63,000 90,00010116 24,000 4.5 3.5 108,000 84,00010117 12,000 5.25 6.25 63,000 75,000
Total 128,000 414,500 525,500
Zip
Locating a Health Care Center Using the “Load-Distance Method” (Slide 2 of 3)
where xf = Distance along the x axis from the origin to the center of gravity yf = Distance along the y axis from the origin to the center of gravity ai = The activity level (load) from the i th location to the proposed facility Xi = the coordinate on the x axis for the i th customer location yi = the coordinate on the y axis for the i th customer location
n
ii
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iii
a
xaxf
1
1
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n
ii
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a
yayf
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Locating a Health Care Center Using the “Load-Distance Method” (Slide 3 of 3)
The coordinates of the center of gravity are:
xf = yf = 414,500 525,500
128,000 128,000
= 3.24 = 4.11
Transportation Problem
Cost of moving materials between multiple destinations
Vogel’s Approximation Method
To evaluate two locations, solve the transportation problem for each location
OR
Transportation Example
New facility capacity = 5000 units/month We must choose either Des Moines, Iowa or
Montgomery, Alabama Transportation costs per unit for Des Moines
and Montgomery to each customer location are provided
We are interested in total transportation cost for Des Moines versus Montgomery
Transportation Example (cont’d)
Supply
Lexington - 12,420
Milan - 9,380
DesMoines - 5,000 (proposed)
or
Montgomery - 5,000 (proposed)
Transportation Example (cont’d)
Demand
Baton Rouge - 6,740
Bismarck - 8,400
Tampa - 5,050
Youngstown - 5,670
DESTINATION
Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE
14 18 16 12 0 12420Lexington
17 15 17 9 0 9380Milan
17 11 19 14 0 5000
DesMoines
6740 8400 5050 5670 940 26800DEMAND
DESTINATION
Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE
14 18 16 12 0 12420 12Lexington
17 15 17 9 0 9380 9Milan
17 11 19 14 0 5000 11DesMoines
6740 8400 5050 5670 940 26800DEMAND
3 4 1 3 0
DESTINATION
Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE
14 18 16 12 0 12420 12Lexington 940
17 15 17 9 0 9380 9Milan
17 11 19 14 0 5000 11DesMoines
6740 8400 5050 5670 940 26800DEMAND
3 4 1 3 0
DESTINATION
Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE
14 18 16 12 0 12420 2Lexington 940 11480
17 15 17 9 0 9380 6Milan
17 11 19 14 0 5000 3DesMoines
6740 8400 5050 5670 940 26800DEMAND 0
3 4 1 3
DESTINATION
Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE
14 18 16 12 0 12420 2Lexington 940 11480
17 15 17 9 0 9380 6Milan 5670
17 11 19 14 0 5000 3DesMoines
6740 8400 5050 5670 940 26800DEMAND 0
3 4 1 3
DESTINATION
Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE
14 18 16 12 0 12420 2Lexington 940 11480
17 15 17 9 0 9380 2Milan 5670 3710
17 11 19 14 0 5000 6DesMoines
6740 8400 5050 5670 940 26800DEMAND 0 0
3 4 1
DESTINATION
Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE
14 18 16 12 0 12420 2Lexington 940 11480
17 15 17 9 0 9380 2Milan 5670 3710
17 11 19 14 0 5000 6DesMoines 5000
6740 8400 5050 5670 940 26800DEMAND 0 0
3 4 1
DESTINATION
Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE
14 18 16 12 0 12420 2Lexington 940 11480
17 15 17 9 0 9380 2Milan 5670 3710
17 11 19 14 0 5000 DesMoines 5000 0
6740 8400 5050 5670 940 26800DEMAND 3400 0 0
3 3 1
DESTINATION
Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE
14 18 16 12 0 12420 2Lexington 6740 940 11480
17 15 17 9 0 9380 2Milan 5670 3710
17 11 19 14 0 5000 DesMoines 5000 0
6740 8400 5050 5670 940 26800DEMAND 3400 0 0
3 3 1
DESTINATION
Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE
14 18 16 12 0 12420 2Lexington 6740 940 4740
17 15 17 9 0 9380 2Milan 5670 3710
17 11 19 14 0 5000 DesMoines 5000 0
6740 8400 5050 5670 940 26800DEMAND 0 3400 0 0
3 1
DESTINATION
Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE
14 18 16 12 0 12420 2Lexington 6740 940 4740
17 15 17 9 0 9380 2Milan 3400 5670 3710
17 11 19 14 0 5000 DesMoines 5000 0
6740 8400 5050 5670 940 26800DEMAND 0 3400 0 0
3 1
DESTINATION
Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE
14 18 16 12 0 12420 Lexington 6740 940 4740
17 15 17 9 0 9380 Milan 3400 5670 310
17 11 19 14 0 5000 DesMoines 5000 0
6740 8400 5050 5670 940 26800DEMAND 0 0 0 0
1
DESTINATION
Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE
14 18 16 12 0 12420 Lexington 6740 4740 940 4740
17 15 17 9 0 9380 Milan 3400 5670 310
17 11 19 14 0 5000 DesMoines 5000 0
6740 8400 5050 5670 940 26800DEMAND 0 0 0 0
1
DESTINATION
Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE
14 18 16 12 0 12420 Lexington 6740 4740 940 0
17 15 17 9 0 9380 Milan 3400 5670 310
17 11 19 14 0 5000 DesMoines 5000 0
6740 8400 5050 5670 940 26800DEMAND 0 0 310 0 0
DESTINATION
Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE
14 18 16 12 0 12420 Lexington 6740 4740 940 0
17 15 17 9 0 9380 Milan 3400 310 5670 310
17 11 19 14 0 5000 DesMoines 5000 0
6740 8400 5050 5670 940 26800DEMAND 0 0 310 0 0
DESTINATION
Baton Rouge Bismarck Tampa Youngstown Dummy CAPACITYSOURCE
14 18 16 12 0 12420 Lexington 6740 4740 940 0
17 15 17 9 0 9380 Milan 3400 310 5670 0
17 11 19 14 0 5000 DesMoines 5000 0
6740 8400 5050 5670 940 26800DEMAND 0 0 0 0 0
Total Transportation Cost for Des Moines6740($14)+4740($16)+940($0)+3400($15)+
310($17)+5670($9)+5000($11) = $332,500
For Next Class Figure Transportation Cost for Montgomery
Which is best choice based on Vogel’s Approximation?
Are there other factors to consider? Montgomery’s Transportation Costs:
– Montgomery to Baton Rouge: $9 per unit– Montgomery to Bismarck: $19 per unit– Montgomery to Tampa: $12 per unit– Montgomery to Youngstown $15 per unit
Location Example - Load Distance Location of a warehouse in Germany Method: Load-Distance Method (a.k.a.:
center-of-gravity method) Customer locations (coordinates) and
demands in units per year are given
CITY Demand ai (units/yr.) Xi Yi
Hamburg 42,000 3.25 7Cologne 22,000 1 4.5Stuttgart 37,000 2.5 2Munich 66,000 4.25 1.25Dresden 45,000 5.75 4.5Berlin 113,000 5.5 6
CITY Demand ai (units/yr.) Xi Yi (ai)(xi) (ai)(yi)
Hamburg 42,000 3.25 7 136,500 294,000 Cologne 22,000 1 4.5 22,000 99,000 Stuttgart 37,000 2.5 2 92,500 74,000 Munich 66,000 4.25 1.25 280,500 82,500 Dresden 45,000 5.75 4.5 258,750 202,500 Berlin 113,000 5.5 6 621,500 678,000
CITY Demand ai (units/yr.) Xi Yi (ai)(xi) (ai)(yi)
Hamburg 42,000 3.25 7 136,500 294,000 Cologne 22,000 1 4.5 22,000 99,000 Stuttgart 37,000 2.5 2 92,500 74,000 Munich 66,000 4.25 1.25 280,500 82,500 Dresden 45,000 5.75 4.5 258,750 202,500 Berlin 113,000 5.5 6 621,500 678,000
TOTAL 325,000 1,411,750 1,430,000
xf =(a )(x )
a
yf =(a )(y )
a
i i
i=1
n
i
i=1
n
i i
i=1
n
i
i=1
n
1 411 750
325 0004 34
1 430 000
325 0004 40
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Show map here
Location?
Central Germany
Other Factors to Consider?
operating costs required investment government incentives qualitative factors overall strategy of organization
Location Decision Affects Other Operating Decisions
Alternative to on-site expansion
On-site expansion is problematic– Material handling and storage
– Complex production flow
– Strained communication
– New technology delayed
– Use of old equipment
– Layering of expanded responsibilities
International Dimensions ofLocation Decision
Reasons for locating in foreign countries
– Comparative Advantage
– Closeness to market
– Political relationships
– Availability of resources
Location Analysis forLocation Analysis forService OperationsService Operations
Concepts and techniques discussed so far apply to service operations
Service issues:» Minimize response time:
Emergency medical services
» Provide minimum coverage: Fire Protection
» Mobile location: Police or security units