Supply Chain Management - 4th edition

Transcript Supply Chain Management - 4th edition

Chapter 5 Network Design in the Supply Chain

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Outline

 The Role of Network Design in the Supply Chain  Factors Influencing Network Design Decisions  Framework for Network Design Decisions  Models for Facility Location and Capacity Allocation  The Role of IT in Network Design  Making Network Design Decisions in Practice Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall.

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Network Design Decisions

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Factors Influencing Network Design Decisions

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Strategic Factors

Factors Influencing Network Design Decisions

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Factors Influencing Network Design Decisions

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Factors Influencing Network Design Decisions

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Factors Influencing Network Design Decisions

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Factors Influencing Network Design Decisions

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Competitor location

Factors Influencing Network Design Decisions

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Service and Number of Facilities

Number of Facilities 5-16

Costs and Number of Facilities

Transportation 5-17

Cost Buildup as a Function of Facilities

Total Costs Number of Facilities

Facilities Inventory Transportation Labor

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Framework for Network Design Decisions

 Phase I – Supply Chain Strategy  Phase II – Regional Facility Configuration  Phase III – Desirable Sites  Phase IV – Location Choices Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall.

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A Framework for Network Design Decisions

GLOBAL COMPETITION Competitive STRATEGY INTERNAL CONSTRAINTS Capital, growth strategy, existing network PRODUCTION TECHNOLOGIES Cost, Scale/Scope impact, support required, flexibility COMPETITIVE ENVIRONMENT PHASE I Supply Chain Strategy PHASE II Regional Facility Configuration TARIFFS AND TAX INCENTIVES REGIONAL DEMAND Size, growth, homogeneity, local specifications POLITICAL, EXCHANGE RATE AND DEMAND RISK PHASE III Desirable Sites AVAILABLE INFRASTRUCTURE PRODUCTION METHODS Skill needs, response time FACTOR COSTS Labor, materials, site specific PHASE IV Location Choices LOGISTICS COSTS Transport, inventory, coordination Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall.

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Linear programming (LP)

LP example (Joe’s chop shop)

 Joe takes plain vans and converts them into custom vans and can produce either fine or fancy vans. Both types require a $25,000 plain van. Fancy vans sell for $37,000 and Joe uses $10,000 in parts to customize them yielding a profit margin of $2,000. Fine vans use $6,000 in parts and sell for $32,700 yielding profits of $1,700. Joe figures the shop can work on no more than 12 vans in a week. Joe hires 7 people including himself and operates 8 hours per day, 5 days a week and thus has at most 280 hours of labor available in a week. Joe also estimates that a fancy van will take 25 hours of labor, while a fine van will take 20 hours.

 To maximize profit, how many of each van should Joe produce?

LP Example (Joe’s chop shop)

LP example (Joe’s chop shop)

 To maximize profit, how many of each van should Joe produce?

LP Example (Joe’s chop shop)

LP example (Joe’s chop shop)

 To maximize profit, how many of each van should Joe produce?

LP Example (Joe’s chop shop)

6 Xfine 8 10 12

LP Example- Excel Solver

Steps to add the Solver add-in in

Excel 2007

1. Click the Microsoft Office Button , and then click Excel Options.

2. Click Add-Ins, and then in the Manage box, select Excel Add-ins.

3. Click Go.

4. In the Add-Ins available box, select the Solver Add-in check box, and then click OK.

Tip: If Solver Add-in is not listed in the Add-Ins available box, click Browse to locate the add-in.

If you get prompted that the Solver Add-in is not currently installed on your computer, click Yes to install it.

LP Example

Maximize Z = 2000 Xfancy + 1700 Xfine # of Fancy produced # of Fine produced Subject to Xfancy + Xfine <= 12 25 Xfancy + 20Xfine <= 280 0 0 Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall.

LP Example

Maximize Z = 2000 Xfancy + 1700 Xfine # of Fancy produced # of Fine produced Subject to Xfancy + Xfine <= 12 25 Xfancy + 20Xfine <= 280 22800 8 4 12 280 Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall.

LP example #2 (calculators)



A calculator company produces a scientific calculator and a graphing calculator. Long-term projections indicate an expected demand of at least 100 scientific and 80 graphing calculators each day. Because of limitations on production capacity, no more than 200 scientific and 170 graphing calculators can be made daily. To satisfy a shipping contract, a total of at least 200 calculators much be shipped each day.



If each scientific calculator sold results in a $2 loss, but each graphing calculator produces a $5 profit, how many of each type should be made daily to maximize net profits?

LP Example #2 (Calculators)

 Maximize Z = -2 X scientific + 5 X graphing  Subject to: X scientific X graphing X scientific + X graphing X scientific X graphing ≥ 100 ≥ 80 ≤ 200 ≤ 200 ≤ 170 Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall.

LP Example #2 (Calculators)

Network Optimization Models

 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?

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Plant Location with Multiple Sourcing

Min i n

  1

f i y i



i m n

  1  1

j c ij x ij s

i n

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x ij



D j

 1 ,...,

m j n

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x ij



K i y i

 1 ,...,

n i m

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y i

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;

y i

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Figure 5-3

Inputs - Costs, Capacities, Demands

Demand Region Production and Transportation Cost per 1,000,000 Units

Fixed Low Fixed High

Supply Region

N. America S. America Europe Asia Africa

Demand

N. America S. America Europe 81 117 92 77 101 108 Asia 130 98 Africa 115 100 102 115 142 12 105 125 100 8 95 90 103 14 119 59 105 16 111 74 71 7

Cost ($) Capacity Cost ($) Capacity

Figure 5-4

Decision Variables

Demand Region - Production Allocation (1000 Units)

Plants Plants

Supply Region

N. America S. America Europe N. America 0 0 0 S. America Europe Asia 0 0 0 0 0 0 0 0 0 Africa 0 0 0 Asia 0 0 0 0 0 Africa 0 0 0 0 0 (1=open) (1=open) 0 0 0 0 0 0 0 0 0 0 Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall.

Figure 5-5

Constraints

Supply Region

N. America S. America Europe Asia Africa

Unmet Demand Excess Capacity

0 0 0 0 0 N. America 12 S. America 8 Europe 14

Objective Function Cost =

Figure 5-6

Figure 5-7

Inputs - Costs, Capacities, Demands

Demand Region Production and Transportation Cost per 1,000,000 Units

Fixed Low Fixed High

Supply Region

N. America S. America Europe Asia Africa

Demand

N. America S. America Europe 81 117 102 115 142 12 92 77 105 125 100 8 101 108 95 90 103 14 Asia 130 98 119 59 105 16 Africa 115 100 111 74 71 7

Cost ($) Capacity Cost ($) Capacity

6,000 10 9,000 20 4,500 6,500 4,100 4,000 10 6,750 10 9,750 10 6,150 10 6,000 20 20 20 20

Decision Variables

Demand Region - Production Allocation (1000 Units) Supply Region

N. America S. America Europe Asia Africa N. America S. America Europe 0 12 0 0 0 0 8 0 0 0 0 0 0 4 10 Asia 0 0 0 16 0 Africa Plants Plants 0 0 7 0 0 (1=open) (1=open) 0 0 0 1 0 0 0 0 1 1

Constraints

Supply Region

N. America S. America Europe Asia Africa

Unmet Demand Excess Capacity

0 0 0 0 3 N. America S. America Europe 0 0 0 Asia

Objective Function Cost =

0 Africa 0

Gravity Method





 1

d nx V n k



 1

V n

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

 1

d ny V n k

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 1

V n

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= (60x5000) + (15x1000) + (80x3000) 5000+ 1000 + 3000 

= (15x5000) + (70x1000) + (110x3000) 5000+ 1000 + 3000 

= 555000/9000 ≈



= 475000/9000 ≈

Gravity Method

30 20 10 70 60 50 40 100 90 80 C C C C

Customer

Gravity Method

 Ton Mile-Center Solution – x : X coordinate center of gravity – y : Y coordinate center of gravity – d nx : X coordinate of the n location th – d ny : Y coordinate of the n location th – V n : Annual tonnage to delivery location n



n k

  1

d nx V n n k

  1

V n y



n k

  1

d ny V n n k

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V n

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



 1

d nx V n k

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 1

V n

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

 1

d ny V n k

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 1

V n

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= (75x500) + (35x2000) + (25x1200) + (65x600) 500+ 2000 + 1200 + 600 

= (40x500) + (40x2000) + (80x1200) + (105x600) 500+ 2000 + 1200 + 600 

= 176500/4300 =



= 259000/4300 =

Gravity Method

Customer

California Texas New York x 60 15 80 y 15 70 110 demand 5000 1000 3000





 1

d nx V n k



 1

V n





 1

d ny V n k

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 1

V n

QUESTION>>>

 QUESTION….

Gravity Method





 1

d nx V n k



 1

V n





 1

d ny V n k



 1

V n

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= (60x5000) + (15x1000) + (80x3000) 5000+ 1000 + 3000 

= (15x5000) + (70x1000) + (110x3000) 5000+ 1000 + 3000 

= 555000/9000 ≈



= 475000/9000 ≈

Exercise #2

 DryIce, Inc., is a manufacturer of air conditioners that ha seen its demand grow significantly. The company anticipates nationwide demand for the year 2010 to be 180,000 in the South, 120,000 units in the Midwest, 110,000 in the East, and 100,000 units in the West. Managers at DryIce are designing the manufacturing network and have selected four potential sites New York, Atlanta, Chicago, and San Diego. Plants could have a capacity of either 200,000 or 400,000 units. The annual fixed costs are the four locations are shown in the table below, along with the cost of producing and shipping an air conditioner to each of the four markets. Where should DryIce build its factories and how large should they be?

New York Atlanta

Fixed Costs 200k

6,000,000 5,500,000 400k 10,000,000 9,200,000

Variable Costs

East South Midwest West 211 232 240 300 232 212 230 280 Chicago 5,600,000 9,300,000 238 230 215 270 San Diego 6,100,000 10,200,000 299 280 270 225

Exercise #2

 Objective function: Minimize Z = fixed costs + Variable costs  Subject to : All shipments are positive integers (≥0) All shipments are ≤ 400000 All shipment add up to the 2010 requirements.

 Question  Answer is:  **265740  250150  231000  276090

Question

New York

Fixed Costs 200k

6,000,000 400k 10,000,000

Variable Costs

Shipped from NY East 211 South 232 -

Exercise #2

Atlanta 5,500,000 9,200,000 110,000 232 212 Shipped from Atlanta Chicago 5,600,000 9,300,000 238 180,000 230 Shipped from Chicago San Diego Shipped from San Diego Requirements 6,100,000 10,200,000 299 280 110,000 180,000 Supply 110,000 180,000 Midwest 240 West 300 230 280 215 270 120,000 270 225 120,000 100,000 100,000 120,000 100,000 Fixed 23,210,000 6,000,000 110,000 38,160,000 5,500,000 180,000 25,800,000 5,600,000 120,000 22,500,000 6,100,000 100,000 29,210,000 43,660,000 31,400,000 28,600,000 132,870,000

TOTAL SYSTEM COST

New York

Fixed Costs 200k

6,000,000 400k 10,000,000

Variable Costs

Shipped from NY East 211 South 232 -

Exercise #2

TOTAL SYSTEM COST

The Role of IT in Network Design

 IT systems help with network design by: 1.

Making the modeling of the network design problems easier Containing high-performance optimization technologies Allowing for “what-if” scenarios Interfacing with planning and operational software Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall.

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Making Network Design Decisions In Practice

 Do not underestimate the life span of facilities  Do not gloss over the cultural implications  Do not ignore quality of life issues  Focus on tariffs and tax incentives when locating facilities Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall.

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Summary of Learning Objectives

 What is the role of network design decisions in the supply chain?

 What are the factors influencing supply chain network design decisions?

 Describe a strategic framework for facility location.

 How are the following optimization methods used for facility location and capacity allocation decisions?

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Supply Chain Management - 4th edition

Transcript Supply Chain Management - 4th edition

Chapter 5 Network Design in the Supply Chain

Outline

Network Design Decisions

Factors Influencing Network Design Decisions

Strategic Factors

Factors Influencing Network Design Decisions

Factors Influencing Network Design Decisions

Factors Influencing Network Design Decisions

Factors Influencing Network Design Decisions

Factors Influencing Network Design Decisions

Competitor location

Competitor location

Competitor location

Factors Influencing Network Design Decisions

Service and Number of Facilities

Costs and Number of Facilities

Cost Buildup as a Function of Facilities

A Framework for Network Design Decisions

Linear programming (LP)

LP example (Joe’s chop shop)

LP Example (Joe’s chop shop)

LP example (Joe’s chop shop)

LP Example (Joe’s chop shop)

LP example (Joe’s chop shop)

LP Example (Joe’s chop shop)

LP Example- Excel Solver

LP Example

LP Example

LP example #2 (calculators)

LP Example #2 (Calculators)

LP Example #2 (Calculators)

Network Optimization Models

Plant Location with Multiple Sourcing

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Figure 5-5

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Gravity Method

Gravity Method

Gravity Method

Gravity Method

Gravity Method

QUESTION>>>

Gravity Method

Exercise #2

Exercise #2

Question

Exercise #2

Exercise #2

The Role of IT in Network Design

Summary of Learning Objectives

Directory