1. Facility Location Evaluating potential sites – non-tangible criteria
Cost – transportation models – Applichem
Service facilities
Issue of cost minimization vs. response speed
Role of inventory

2. Plant Location Methodology: Factor Rating Method Example
Two refineries sites (A and B) are assigned the following range of point values and respective points, where the more points the better for the site location.
Sites
A B
Major factors for site location
Pt. Range
123
150 54 24 45 34 8
156
100 63 96 55 14 4 50 20
Best Site is B
Total pts

3. Plant Location Methodology: Transportation Method of Linear Programming
Transportation method of linear programming seeks to minimize costs of shipping n units to m destinations or it seeks to maximize profit of shipping n units to m destinations.

4. Applichem – Steps to solve
1. Calculate cost/1,000 units for each alternative (matrix).
2. Calculate total cost/alternative matrix.
3. Calculate total cost of current solution.
4. Solver setup
-Target Cell
-Minimize
-Capacity Constraints
-Demand Constraints
-Options
Linear Solution
Non-Negative
-Solve

5. Locating Service Facilities
Site screening using regression analysis
Profitability = a + b1 x1 + b2 x2 + b3 x3
Variables to include in the model (dependent on situation):
Median income of local population
Local population size
Traffic in front of site
Categories of variables: competitive, demand, demographic, physical access.

6. Matching Supply-Chains with Products
Innovative
Products
Functional
Products
Efficient
Supply-Chain
Match
Mismatch
Responsive
Supply-Chain
Mismatch
Match
Marshall Fisher – Efficient vs Responsive Supply Chains

7. Demand Characteristics Supply Characteristics
Functional
Innovative
Stable
Evolving
Low demand uncertainty
More predictable demand
Stable demand
Long product life
Low inventory cost
Low profit margin
Low product variety
Higher volume
Low stockout cost
Low obsolescence
High demand uncertainty
Difficult to forecast
Variable demand
Short selling season
High inventory cost
High profit margin
High product variety
Low volume
High stockout cost
High obsolescence
Less breakdowns
Stable and higher yields
Less quality problems
More supply sources
Reliable suppliers
Less process changes
Less capacity constraints
Easier to changeover
Flexible
Dependable lead times
Vulnerable to breakdowns
Variable and lower yields
Potential quality problems
Limited supply sources
Unreliable suppliers
More process changes
Potential capacity constrained
Difficult to changeover
Inflexible
Variable lead time

8. Low (Functional Products) High (Innovative Products)
Demand Uncertainty
Low (Functional Products)
High (Innovative Products)
Supply Uncertainty
Low (Stable Process)
Grocery, basic apparel, food, oil and gas
Efficient Supply Chain
Fashion apparel, computers, popular music
Responsive Supply Chain
High (Evolving Process)
Hydro-electric power, some food produce
Risk-Hedging Supply Chain
Telecom, high-end computers, semiconductor
Agile Supply Chain
Hau Lee’s Uncertainty Framework – Examples and Types of Supply Chain Needed

9. Automobile Manufacturing
What type of supply chain are these companies opting for these days?
Efficient, Responsive, Risk Hedging, Agile
Ford
BMW
Mercedes Benz GM
Honda

10. Faraway Factories
Global auto makers increasingly are using remote plants in the developing world to make cars for their home markets. Here are some of the latest examples:
1. Ford in Bahia: Fusion mini-SUV for U.S. (starting 2004)
2. BMW in Rosslyn: 3-series sedans for Japan, Australia, U.S.
3. Volkswagen in Uitenhage: Golf compacts for Europe
4. DaimlerChrysler in East London: Mercedes C-class sedans for Europe
5. Honda in Ayutthaya: unnamed compact car for Japan (starting late 2002)
6. GM in Rayong: Opel Zafira minivans for Europe, Japan
7. Honda in Guangzhou: unnamed cars for Europe and Asia (starting 2004)
Source: the companies

11. Concluding Remarks
Struggle between low cost labor and transportation to market.
Response is a function of distance to market vs inventory carried locally.
Labor productivity is largely a function of automation.
Automation greatly impacts flexibility.
Global producers have a global set of alternatives to consider.
Very rich area for analysis – no shooting from the hip here.