8

Network operation planning Network design problems Network design and operations models:

extension Data for network design Strategic role of units in the network Locations of service systems

Design : Location and capacity of plants and distribution centres ( warehouses) so as to serve customers in a cost-effective way Strategic decision Relevant cost : Facility cost, Variable

production cost, Transportation cost Operations: For a given design decide

optimal linkages between plants and markets Tactical decision Relevant cost : Variable production cost,

Transportation cost

Indian Paints: Five Plants and Six Markets

Indian Paints: Production Plus Transportation Cost*

*per unit

M= Number of plants. Let i= 1..m describe m respective manufacturing plants.

N= Number of markets. Let j= 1..n describe n respective markets Demj , Pricej , = demand & Price at market j

Capi = production capacity at plant i

Costij = Cost of producing and transporting one unit from plant i to market j

F costi = Fixed cost of facility i

Decision Variables:

Quantij = Quantity shipped from plant i to market j

Fac open i = 0 or 1 binary variable for facility i - If binary value is 1

:facility is open and If binary value is 0 :facility is close* Parameters in italic type and blue are used in design decisions. Capacity and demand are for unit time period. Unit time period

could be month, quarter or a year

m

i

n

j

ijij QuantCost1 1

*

jm

iij DemQuant

1

in

jij CapQuant

1

0ijQuant

Subject to following constraints:

for j=1..n for i=1…m

for i=1..m , j=1..n

Network Operations Planning: Cost Minimization Model

Minimize

Number of variables= m *n & number of constraints= m+n

Objective function value= Total Variable costs=773,770Revenue= 1,017,450 , Gross Profit = 243,680 , Net Profit= 15,680

Network Operations Planning: Cost Minimization Model

m

i

n

jijijij

m

ij

n

jQuantCostQuantice

1 1*

1 1*Pr

j

m

i

ij DemQuant 1

i

n

j

ij CapQuant 1

0ijQuant

Maximise

for i=1…m

for j=1..n

for i=1..m , j=1..n

Network Operations Planning: Profit Maximization Model

Number of variables= m *n & number of constraints= m+n

Objective Function = Maximize Total Gross Profit = 245230 Revenue= 885700 Variable cost = 640470, Net Profit= 17,230

Network Operations Planning: Profit Maximization Model

Decision problem

Type of decision

Objective Revenue Net Profit % Net profit/Sales

I Network Operations

Cost Minimisation

1017450 15680 1.54

II Network Operations

Profit Maximisation

885700 17230 1.95

Why is Kolkata market not served in model II ?

Change in market structure Change in market demand Changes in wage rate Changes in utilities and cost of

transportation

m

i

n

jijijii QuantCosttFopenFac

1 1*cos

jm

iij DemQuant

1

iin

jij CapopenFacQuant

1

0

,10

Quantij

oropenFac i

Subject to following constraints:

for j=1..n for i=1…m

for i=1..m , j=1..n

Network Design: Cost Minimization ModelMinimize

Number of linear variables= m *n, number of binary variables=m & number of constraints= m+n

For i= 1..m

Bangalore Chennai Delhi Mumbai Lucknow Kolkata

Supply Plant

(open/close)

Ahmedabad 0 0 0 0 0 0 0 No

Baddi 0 0 280 0 120 0 400 Yes

Hubli 165 135 0 60 0 0 360 Yes

Nagpur 0 0 0 140 5 155 300 Yes

Vishakapatna

m 0 0 0 0 0 0 0

No

Supply 165 135 280 200 125 155 0

Network Design: Cost Minimization Model

Objective function = Total Costs ( Fixed + Variable) = 891760Revenue= 1,017,450 , Gross Profit = 241,690 , Net Profit= 125,690

m

i

n

jQuantCostOpenFacQuant

m

iice

n

jijijiijj

1 1**

1Pr

1

Maximise

for i=1…m

for j=1..n

for i=1..m , j=1..n

Network Operations Planning: Profit Maximization Model

0

,10

Quantij

oropenFac i

iin

jij CapopenFacQuant

1

j

m

i

ij DemQuant 1

for i=1…m

Number of linear variables= m *n, number of binary variables=m & number of constraints= m+n

Bangalore Chennai Delhi Mumbai Lucknow Kolkata

Supply Plant

(open/close)

Ahmedabad 0 0 0 0 0 0 0 No

Baddi 0 0 280 0 120 0 400 Yes

Hubli 165 85 0 200 0 0 450 Yes

Nagpur 0 0 0 0 0 0 0 No

Vishakapatn

am 0 0 0 0 0 0

0 No

Supply 165 85 280 200 120 0

Objective function = Total Net Profit = 154,685Revenue= 833,700 , Variable Cost = 601,015 Gross Profit= 232, 685

Network Design: Profit Maximization Model

Fixed Cost= 78,000

A Performance Comparison of the Four Models

-Under what circumstances Indian paints choose not to use model IV ?- How do choice of organisation structure affect selection of model ?

Handling new/Strategic markets Handling Seasonal products

Including Inventory in model Handling Multiple capacity option in network

design decisions Handling Short life cycle products

Cost versus time trade offs Cycle time Weighted activity time

Incorporating Uncertainty

DISK(Malasiya or Germany)

Motherboard(Mexico or

China)

PC assembly(Canada or

Taiwan)

Market(India)

Demand Aggregate products and customers

Production Cost Comparable costs across facilities

Transportation costs Time horizon

SOURCE

OUTPOSTOFFSHORE

LEADCONTRIBUT

OR

SERVER

SRATEGIC REASON FOR PLANT

STR

ATE

GIC

R

OLE

Access to low cost

resources

HIGH

LOWAccess to

skillsAccess to markets

STRETEGIC ROLE OF UNIT IN THE NETWORK

Offshore facility – labour, RM Server facility- market Outpost facility- Skills , knowledge Source: Serving global market Contributor- contributes to product and

process innovations Lead: leader in product and process

innovationsSource: Ferdow – HBR(1997)

Offshore –To gain access to low wages or other factors integral to low-cost production

Server- Serves specific national or regional markets

Outpost – To gain access to the knowledge or skills

Source: Ferdows (HBR 1997)

Source- Strategic Role Broader than offshore unit. Has a global responsibility for a part or a product

Contributor- Serves local market but also assumes responsibility for product customization , process improvements.

Lead- Ability and knowledge to create new products, processes, and technologies for the company

Source: Ferdows (HBR 1997)

Market coverage gets affected by location decision Retail outlets Impact of ownership structure

Emergency systems CTC at Bangalore ( Operation Sanjeevani)

Guaranteed delivery time After-market service

Public systems Equity issues