(3)WHAT IS A SUPPLY CHAIN

S ^UPPLY C ^HAIN

M ^ANAGEMENT , F ^ACILITY C ^APACITY , L ^OCATION , ^AND

L ^AYOUT

Unit III

S

UPPLY CHAIN MANAGEMENT

 A supply chain is the interrelated series of processes within a firm or across different firms that produces a service or product to the satisfaction of customers.

 SCM is the synchronization of a firm’s processes with those of its suppliers and customers to match flow of materials, services, and information with demand.

W

HAT IS A

S

UPPLY

C

HAIN

?

 All stages involved, directly or indirectly, in fulfilling a customer request

 Includes manufacturers, suppliers, transporters, warehouses, retailers, and customers

 Within each company, the supply chain includes all functions involved in fulfilling a customer request (product development, marketing, operations, distribution, finance, customer service)

W

HAT IS A

S

UPPLY

C

HAIN

?

 The different stages of supply chain are:

 Customers

 Retailers

 Wholesalers/distributors

 Manufacturers

 Component/Raw material suppliers

All stages may not be present in all supply chains (e.g., no retailer or distributor for Dell)

 A supply chain is dynamic.

 It involves constant flow of information, products and funds at different stages.

F

LOWS IN A

S

UPPLY

C

HAIN

Figure 1-2

S

UPPLY

C

HAIN FOR SERVICES



SC design for services is driven by the need to provide support for the essential elements of various services it delivers.



SC plays an integrated role in its

ability to meet competitive priorities

such as top quality, delivery speed,

and customization.

S

^ERVICE

S

^UPPLY

C

^HAIN

Home

customers Commercial

customers Flowers-on-Demand florist

Packaging Flowers:

Local/Internati onal

Arrangem materials ent FedEx

delivery service

Local delivery

service

Internet service Maintenan

ce services

S

UPPLY

C

HAIN FOR

M

ANUFACTURING



The purpose of SC design for manufacturers is to control inventory by managing the flow of materials.



A typical manufacturer spends more than 60% of its total income on purchased services and materials. This percentage is only 30-40% in case of a service provider.



Manufacturers can reap large profits

with a small reduction in the cost of

materials by focusing on their SCs.

M

ANUFACTURING

S

^UPPLY

C

^HAIN

East Coast West Coast East Europe West Europe Retail

USA Ireland Distribution

centers Manufacturer

USA Assembly

Poland USA Canada Australia Malaysia

Tier 3 Raw

materia ls

Germany Mexico USA China

Tier 2 Components

Germany Mexico USA

Tier 1 Major

subassemblies

T

HE

O

BJECTIVE OF A

S

UPPLY

C

HAIN

 Maximize overall value created

Supply Chain Surplus

= Customer Value – Supply Chain Cost

The value a supply chain generates is the

difference between what the final product is

worth to the customer and the costs the

supply chain incurs in filling the customer’s

request.

T

HE

O

BJECTIVE OF A

S

UPPLY

C

HAIN

 Example: a customer purchases a wireless router from Best Buy for $60 (revenue)

 Supply chain incurs costs (information,

storage, transportation, components, assembly, etc.)

 Difference between $60 and the sum of all of these costs is the supply chain profit

 Supply chain profitability is total profit to be shared across all stages of the supply chain

 Success should be measured by total supply chain profitability, not profits at an individual stage

P

^ROCESS

V

^{IEW OF A}

S

^UPPLY

C

^HAIN

 Cycle View: processes in a supply chain are divided into a series of cycles, each performed at the interfaces between two successive supply chain stages

 Push/Pull View: processes in a supply chain are divided into two categories depending on whether they are executed in response to a customer order (pull) or in anticipation of a customer order (push)

C

YCLE

V

IEW OF

S

UPPLY

C

HAIN

P

ROCESSES

P

^USH

/P

^ULL

V

^{IEW OF}

S

^UPPLY

C

^HAINS

P

USH

/P

ULL

V

IEW OF

S

UPPLY

C

HAIN

P

ROCESSES

 Supply chain processes fall into one of two categories depending on the timing of their execution relative to customer demand

 Pull: execution is initiated in response to a customer order (reactive)

 Push: execution is initiated in anticipation of customer orders (speculative)

 Push/pull boundary separates push processes from pull processes

S

TRATEGIC

O

PTIONS FOR

S

UPPLY

C

HAIN

D

ESIGN

 Efficient supply chains - These supply chains works best in environments where demand is highly predictable. The focus is on efficient service, material and information flows.

 Make-to-stock (MTS)

 Responsive supply chains – These supply chains are designed to react quickly to demand.

 Assemble-to-order (ATO)

 Make-to-order (MTO)

 Design-to-order (DTO)

E

NVIRONMENTS

Factor Efficient Supply

Chains Responsive Supply Chains

Demand Predictable, low forecast

errors Unpredictable, high forecast errors Competitive

priorities Low cost, consistent quality, on-time

delivery

Development speed, fast delivery times,

customization, volume flexibility, variety, top

quality service/product New-

introduction

Infrequent Frequent

Contribution

margins Low High

Product

variety Low High

D

^ESIGN

F

^EATURES

Factor Efficient Supply

Chains Responsive Supply Chains

Operation

strategy Make-to-stock or

standardized services or products; emphasize

high volumes

Assemble-to-order, make- to-order, or customized

service or products;

emphasize variety Capacity

cushion Low High

Inventory

investment Low; enable high

inventory turns As needed to enable fast delivery time

Lead time Shorten, but do not

increase costs Shorten aggressively Supplier

selection Emphasize low prices, consistent quality, on-

time delivery

Emphasize fast delivery time, customization, variety, volume flexibility,

top quality

S

UPPLY

C

HAIN

D

ESIGNS

Component

Supplier Manufacturer Finished Goods Inventory

Customer

Supply to forecasted demand

Supply to forecast

Ship to order Customer order Order based on

forecast Order based on

forecast

Make-to-Stock Strategy

S

UPPLY

C

HAIN

D

ESIGNS

Component Supplier

Standardized Component

Inventory

Fabrication Customer

Supply as needed

Customer order Order based on

forecast

Assemble-to-Order Strategy

Assembly

Supply as needed

Supply to Forecasted

Demand

C ^APACITY P ^LANNING

•

Capacity is the maximum rate of output of a process or a system.

•

Capacity planning helps in meeting current and future demand.

•

Acquisition of new capacity requires extensive planning, significant expenditure of resources and time.

•

Capacity decisions involve long term issues like firm’s economies, and trade-offs between customer service and capacity utilization.

M

^{EASURES OF}

C

^{APACITY AND}

U

^TILIZATION

 No single measure of capacity is best for all situations.

 A retailer measures capacity as annual sales value generated per square feet whereas an airline measures capacity as available seat- miles.

 There are two ways of measuring capacity:

 Output Measures of Capacity

 Input Measures of Capacity

M

^{EASURES OF}

C

^{APACITY AND}

U

^TILIZATION

 Output Measures of Capacity –

 This method is best used when firm provides relatively small number of standardized services or products.

 For example, in car manufacturing, capacity can be measured in number of cars produced per day.

 Input Measure of Capacity -

 This method is generally used for low-volume, and flexible processes.

 For example, furniture maker, may measure capacity in terms of inputs such as number of workstations or number of workers.

M

^{EASURES OF}

C

^{APACITY AND}

U

^TILIZATION

Utilization

 It is the degree to which a resource such as equipment, space or workforce is being used.

 It is measured as the ratio of average output rate to maximum capacity.

 It helps in determining how much additional capacity is required or extra capacity that has to be eliminated.

Utilization =  100% Average output rate Maximum capacity

C ^APACITY P ^LANNING ( ^LONG

TERM )



Long term capacity planning involves:

 Economies and diseconomies of scale.

 Capacity timing and sizing strategies.

 Systematic approach to capacity decisions.

E

^{CONOMIES AND}

D

ISECONOMIES OF

S

^CALE

Economies of Scale

 It states that the average unit cost of a service or product can be reduced by increasing its output rate.

 Four principal reasons are:

 Spreading fixed costs

 Reducing construction costs

 Cutting costs of purchased materials

 Finding process advantages

E

^{CONOMIES AND}

D

ISECONOMIES OF

S

^CALE

Diseconomies of Scale

 As the volume increases beyond a certain point, the average cost per unit starts increasing.

 The principal reasons are:

 Complexity

 Loss of focus

 Inefficiencies

E

CONOMIES AND

D

ISECONOMIES OF

S

CALE

C

^APACITY

T

^{IMING AND}

S

^IZING

S

^TRATEGIES

 Sizing Capacity Cushions

 Timing and Sizing Expansion

 Linking Process Capacity and Other Decisions

S

^IZING

C

^APACITY

C

^USHIONS

 Capacity cushions – the amount of reserve capacity a process uses to handle sudden increases in demand or temporary losses of production capacity.

 It measures the amount by which the average utilization (in terms of total capacity) falls below 100 percent.

 When demand varies, large cushions are preferred.

S

IZING

C

APACITY

C

USHIONS

 Capacity cushion =

100% – Average Utilization rate (%)

 Capacity cushions vary with industry

 Capital intensive industries, such as Paper industry, prefer cushions well under 10 percent while hotel industry can live with 30 to 40 percent cushion.

 If a firm experiences high overtime costs and frequently needs to rely on subcontractors, it needs to increase its capacity.

C

^APACITY

T

^{IMING AND}

S

^IZING

•Timing means when to adjust capacity levels and sizing means by how much.

•There are two extreme strategies for expanding capacity:

• Expansionist strategy;

• Wait-and-see strategy

•

The Expansionist strategy stays ahead of demand and minimizes the chances of sales lost to insufficient capacity.

•

The Wait-and-see strategy lags behind demand. To meet any shortfalls, it relies on short-term options, such as, use of overtime, temporary workers, subcontractors, stock-outs, and postponements of maintenance.

C

APACITY

T

IMING AND

S

IZING

Planned unused capacity

Time

Capacity

Forecast of capacity required

Time between increments

Capacity increme nt

(a) Expansionist strategy

Time

Capacity

(b) Wait-and-see strategy

Planned use of short-term

options

Time between increments

Capacity increme nt

C

APACITY

T

IMING AND

S

IZING

Forecast of capacity required

C

^APACITY

T

^{IMING AND}

S

^IZING

 Expansion can result in economies of scale and a faster learning curve.

 It helps in reducing cost and leads to competition on price.

 The wait-and-see strategy reduces the risk of overexpansion, and use of obsolete technology.

 Management can choose any strategy between these two strategies. An intermediate strategy could be follow-the-leader strategy.

L

^INKING

C

^{APACITY AND OTHER}

DECISIONS



Capacity decisions are linked with other decisions that managers take like decisions about designing processes, determining degree of resource flexibility and inventory, and locating facilities.



Capacity cushion can be lowered if less

emphasis is placed on fast deliveries, or if

investment in capital intensive

equipment increases or if worker

flexibility increases.

A S

^YSTEMATIC

A

^{PPROACH TO}

L

^ONG

- T

^ERM

C

^APACITY

D

^ECISIONS

1.

Estimate future capacity requirements

2.

Identify gaps by comparing requirements with available capacity

3.

Develop alternative plans for reducing the gaps

4.

Evaluate each alternative, both

qualitatively and quantitatively, and

make a final choice

S

^TEP

1 - E

^STIMATE

C

^APACITY

R

EQUIREMENTS For one service or product processed at one operation with

a one year time period, the capacity requirement, M, is

Capacity

requirement =

Processing hours required for year’s demand

Hours available from a single capacity unit (such as an employee or machine) per

year, after deducting desired cushion

M = Dp

N[1 – (C/100)]

Where D = demand forecast for the year (number of customers served or units produced)

p = processing time (in hours per customer served or unit produced)

N = total number of hours per year during which the process operates

C = desired capacity cushion (expressed as a percent)

S

^TEP

1 - E

^STIMATE

C

^APACITY

R

EQUIREMENTS

Setup times may be required if multiple products are produced

Capacity

requirement =

Processing and setup hours required for year’s demand, summed over all services

or products

Hours available from a single capacity unit per year, after deducting desired

cushion

M =

[Dp + (D/Q)s]_{product 1} + [Dp + (D/Q)s]_{product 2} + … + [Dp + (D/Q)s]_{product n}

N[1 – (C/100)]

where

Q = number of units in each lot

s = setup time in hours per lot

E

XAMPLE

A copy center in an office building prepares bound reports for two clients. The center makes multiple copies (the lot size) of each report. The processing time to run, collate, and bind each copy depends on, among other factors, the number of pages. The center operates 250 days per year, with one 8-hour shift. Management believes that a capacity cushion of 15 percent (beyond the allowance built into time standards) is best. It currently has three copy machines. Based on the following information, determine how many machines are needed at the copy center.

Item Client

X Client Y Annual demand forecast (copies) 2,000 6,000 Standard processing time

(hour/copy) 0.5 0.7

Average lot size (copies per

report) 20 30

Standard setup time (hours) 0.25 0.40

E

XAMPLE

M =

[Dp + (D/Q)s]_{product 1} + [Dp + (D/Q)s]_{product 1} + … + [Dp + (D/Q)s]_{product n}

N[1 – (C/100)]

= [2,000(0.5) + (2,000/20)(0.25)]_{client X}+ [6,000(0.7) + (6,000/30)(0.40)] _{client Y} [(250 day/year)(1 shift/day)(8 hours/shift)][1.0 - (15/100)]

= = 3.12 5,305 1,700

Rounding up to the next integer gives a requirement of four machines.

S

TEP

2 - I

DENTIFY

G

APS



Identify gaps between projected capacity requirements ( M ) and current capacity



Complicated by multiple operations

and resource inputs

S

TEPS

3

AND

4 –

D

EVELOP AND

E

VALUATE

A

LTERNATIVES

Base case is to do nothing and suffer the consequences

Many different alternatives are possible



Qualitative concerns include strategic fit and uncertainties.



Quantitative concerns may include cash

flows and other quantitative measures.

T

OOLS FOR

C

APACITY

P

LANNING

 Waiting-line models

 Useful in high customer-contact processes



Simulation

 Useful when models are too complex for waiting-line analysis



Decision trees

 Useful when demand is uncertain and sequential decisions are involved

D

ECISION

T

REES

1

Low demand [0.40]

High demand [0.60]

Low demand [0.40]

High demand [0.60]

$70,000

$220,000

$40,000

$135,000

$90,000 Do not expand

Expand

2

$135,000

$109,000

$148,000

$148,000

W ^{HAT IS A} F ^ACILITY L ^OCATION ?

Facility Location

The process of determining geographic sites for a firm’s operations.

Location of a business’s facility has a significant impact on:

•Operating costs,

•Prices it charges,

•Ability to compete in the market, and

•Ability to enter new market segments.

F

ACTORS

A

FFECTING

L

OCATION

D

ECISIONS

Dominant Factors in Manufacturing

 Favorable Labor Climate – more important for labour intensive firms like textiles, furniture, etc.

 Proximity to Markets – Locating near markets is important when final goods are bulky and outbound transportation costs are more.

 Impact on Environment – Polluting industries should locate far-off from cities.

 Quality of Life – More than 50% of new industries in US are coming up in non-urban regions.

F

ACTORS

A

FFECTING

L

OCATION

D

ECISIONS

Dominant Factors in Manufacturing

 Proximity to Suppliers and Resources –When firms depend on bulky inputs or perishable raw materials, or the inbound transportation costs are high.

 Proximity to the Parent Company’s Facilities – better for coordination and communication.

 Utilities, Taxes, and Real Estate Costs – for example BMW established a plant in South Carolina in 1990s.

 Other Factors – Room for expansion, construction costs, accessibility to multiple modes of transportation, insurance costs, competition, community attitude, local laws and others.

F

ACTORS

A

FFECTING

L

OCATION

D

ECISIONS

Dominant Factors in Services

Proximity to Customers – Proximity to customers is the key to success in service sector.

Transportation Costs and Proximity to Markets – By having a warehouse nearby, a firm can hold inventory closer to the customer for making faster delivery.

Location of Competitors – Critical mass is the situation in which several competing firms cluster together in one location and attract more customers than they can do separately.

Site-Specific Factors – Residential density, site visibility, traffic flow and retail activity.

L

OCATION

D

ECISIONS

 Long-term decisions

 Decisions made infrequently

 Decision greatly affects both fixed and variable costs

 Once committed to a location, many resource and cost issues are

difficult to change

S

^ELECTING

F

^{ACILITY LOCATION}

 Based on capacity planning, the management may decide to expand onsite, build another facility, or relocate to another site.

 Onsite expansion results in synergies and reduction in construction costs and time.

 Building a new plant reduces dependence on a single facility and reduction in transportation costs.

 Relocation is mostly done by small firms and more than 80% of relocation are made within 20 miles of companies original location.

M

^ETHODS

 Methods of Evaluating Location Alternatives

 The Factor-Rating Method

 Center-of-Gravity Method

 Locational Break-Even Analysis

 Transportation Model

F

ACTOR RATING METHOD

 When a firm evaluates a large number of locations, it may be useful to streamline the process.

 The step required in determining the factor rating are:

 Identify factors relevant for location rating

 Assign weights to these factors

 Rate the location on various factors, using a suitable rating scale.

 For each factor multiple the factor rating with the factor weight to get the factor score

 Add all the factor scores to get the overall location rating.

C

ONSTRUCTION OF A RATING INDEX

Factors Weights Rating

(VG 5, G 4, A 3, P 2, VP 1)

Score

Input availability 0.25 3 .75

Technical Know how 0.10 4 .40

Reasonableness of cost 0.05 4 .20

Adequacy of markets 0.15 5 .75

Dependence on firm

strategies 0.25 3 .75

Consistency with govt.

policies

0.20 3 .60

Factor Score for the Location 3.45

Using a hurdle rate of 4 we will reject this location.

C

ONSTRUCTION OF A RATING INDEX

Using factor rating methods, which location is most suitable?

 A life insurance company is considering opening an office in two locations, Pune and Mumbai. The factor ratings for the two cities are given:

Factor Weight Pune Mumbai

Customer

convenience .25 70 80

Bank Accessibility .20 40 90

Computer support .20 85 75

Rental Costs .15 90 55

Labour Costs .10 80 50

Taxes .10 90 50

L ^OAD -D ^ISTANCE M ^ETHOD

 Load-Distance Method

 A mathematical model used to evaluate locations based on proximity factors.

 A load may be shipment from suppliers, shipments between plants or to customers, or it may be customers or employees travelling to and from the facility.

 Euclidean distance

 The straight line distance, or shortest possible path, between two points

 Rectilinear distance

 The distance between two points with a series of 90-degree turns, as along city blocks

D

^ISTANCE

What is the distance between (20, 10) and (80, 60)?

Euclidean distance:

d_AB = (x_A – x_B)² + (y_A – y_B)² = (20 – 80)² + (10 – 60)² = 78.1 Rectilinear distance:

d_AB = |x_A – x_B| + |y_A – y_B| = |20 – 80| + |10 – 60| = 110

L

^OAD

-D

^ISTANCE

M

^ETHOD

• Calculating a load-distance score

– Varies by industry

– Use the actual distance to calculate ld score

– Use rectangular or Euclidean distances

– Find one acceptable facility location that minimizes the ld score

• Formula for the ld score

ld =



l_id_i

i

E

^XAMPLE

Management is investigating which location would be best to position its new plant relative to two suppliers (located in Vegas and Toledo) and three market areas (represented by New York, Dayton, and Lima). Management has limited the search for this plant to those five locations. The following information has been collected. Which is best, assuming rectilinear distance?

Location x,y coordinates Trips/year

New York (11,6) 15

Dayton (6,10) 20

Vegas (14,12) 30

Toledo (9,12) 25

Lima (13,8) 40

Location x,y

coordinates Trips/year

New York (11,6) 15

Dayton (6,10) 20

Vegas (14,12) 30

Toledo (9,12) 25

Lima (13,8) 40

15(9) + 20(0) + 30(10) + 25(5) + 40(9) = 920 15(9) + 20(10) + 30(0) + 25(5) + 40(5) = 660 15(8) + 20(5) + 30(5) + 25(0) + 40(8) = 690 15(4) + 20(9) + 30(5) + 25(8) + 40(0) = 590 15(0) + 20(9) + 30(9) + 25(8) + 40(4) = 810 New York =

Dayton = Vegas = Toledo = Lima =

C

^{ENTER OF}

G

^RAVITY

– A good starting point to evaluate locations in the target area using the load-distance model.

– Find x coordinate, x*, by multiplying each point’s x coordinate by its load (l_t), summing these products

l_i x_i, and dividing by l_i

– The center of gravity’s y coordinate y* found the same way

x* =

^l_i ^x_i

l_i

i i

y* =

^l_i ^y_i

l_i

i i

E

^XAMPLE

1

A supplier to the electric utility industry produces power generators;

the transportation costs are high. One market area includes the lower part of the Great Lakes region and the upper portion of the southeastern region. More than 600,000 tons are to be shipped to eight major customer locations as shown below:

Customer Location Tons Shipped x, y Coordinates

Three Rivers, MI 5,000 (7, 13)

Fort Wayne, IN 92,000 (8, 12)

Columbus, OH 70,000 (11, 10)

Ashland, KY 35,000 (11, 7)

Kingsport, TN 9,000 (12, 4)

Akron, OH 227,000 (13, 11)

Wheeling, WV 16,000 (14, 10)

Roanoke, VA 153,000 (15, 5)

E

^XAMPLE

What is the center of gravity for the electric utilities supplier?

Customer

Location Tons

Shipped x, y Coordinates Three

Rivers, MI 5,000 (7, 13) Fort Wayne,

IN 92,000 (8, 12)

Columbus,

OH 70,000 (11, 10) Ashland, KY 35,000 (11, 7) Kingsport,

TN 9,000 (12, 4)

Akron, OH 227,000 (13, 11) Wheeling,

WV 16,000 (14, 10) Roanoke, VA 153,000 (15, 5)

The center of gravity is

calculated as shown below:

x* = =

^l_i ^x_i

^l_i

i i

^l_i =

^li _i ^x_i ⁼ i

5 + 92 + 70 + 35 + 9 + 227 + 16 + 153 = 607

5(7) + 92(8) + 70(11) + 35(11) + 9(12) + 227(13) + 16(14) + 153(15) = 7,504

= 12.4 7,504

607

E

^XAMPLE

y* = =

^l_i ^y_i

^l_i

i i

^l_i ^y_i ⁼

i

5(13) + 92(12) + 70(10) + 35(7) + 9(4) + 227(11) + 16(10) + 153(5) = 5,572

= 9.2 5,572

607

What is the center of gravity for the electric utilities supplier?

Customer

Location Tons

Shipped x, y Coordinates Three

Rivers, MI 5,000 (7, 13) Fort Wayne,

IN 92,000 (8, 12)

Columbus,

OH 70,000 (11, 10) Ashland, KY 35,000 (11, 7) Kingsport,

TN 9,000 (12, 4)

Akron, OH 227,000 (13, 11) Wheeling,

WV 16,000 (14, 10) Roanoke, VA 153,000 (15, 5)

E

^XAMPLE

The resulting load-distance score is

ld =  ^l_i^d_i =

i 5(5.4 + 3.8) + 92(4.4 + 2.8) + 70(1.4 + 0.8) + 35(1.4 + 2.2) + 90(0.4 + 5.2) + 227(0.6 + 1.8) + 16(1.6 + 0.8) + 153(2.6 + 4.2)

= 2,662.4

where d_i = |x_i – x*| + |y_i – y*|

Using rectilinear

distance, what is the

resulting load–distance score for this location?

Customer

Location Tons

Shipped x, y Coordinates Three

Rivers, MI 5,000 (7, 13) Fort Wayne,

IN 92,000 (8, 12)

Columbus,

OH 70,000 (11, 10) Ashland, KY 35,000 (11, 7) Kingsport,

TN 9,000 (12, 4)

Akron, OH 227,000 (13, 11) Wheeling,

WV 16,000 (14, 10) Roanoke, VA 153,000 (15, 5)

E

^XAMPLE

2

A firm wishes to find a central location for its service. Business forecasts indicate travel from the central location to New York City on 20 occasions per year. Similarly, there will be 15 trips to Boston, and 30 trips to New Orleans. The x, y-coordinates are (11.0, 8.5) for New York, (12.0, 9.5) for Boston, and (4.0, 1.5) for New Orleans. What is the center of gravity of the three demand points?

x* = =

^l_i ^x_i

^l_i

i i

y* = =

^l_i ^y_i

^l_i

i i

[(20  11) + (15  12) + (30  4)]

(20 + 15 + 30) = 8.0 [(20  8.5) + (15  9.5) + (30  1.5)]

(20 + 15 + 30) = 5.5

L

OCATIONAL

B

REAK

-E

VEN

A

NALYSIS

 Method of cost-volume analysis used for industrial locations

 Three steps in the method

1. Determine fixed and variable costs for each location

2. Plot the cost for each location

3. Select location with lowest total cost for expected production volume

L

OCATIONAL

B

REAK

-E

VEN

A

NALYSIS

E

XAMPLE

Three locations:

Akron $30,000 $75 $180,000

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

Chicago $110,000 $25 $160,000

Fixed Variable Total

City Cost Cost Cost

Total Cost = Fixed Cost + (Variable Cost x Volume) Selling price = $120

Expected volume = 2,000 units

L

OCATIONAL

B

REAK

-E

VEN

A

NALYSIS

E

XAMPLE

$180,000 – –

$160,000 – –

$150,000 –

$130,000 – –

$110,000 – – – –

$80,000 –

$60,000 – – – –

$30,000 –

$10,000 – – –

Annual cost

| | | | | | |

0 500 1,000 1,500 2,000 2,500 3,000 Volume

Akron lowest cost

Bowling Green lowest cost

Chicago lowest cost

E

^XAMPLE

2

An operations manager narrowed the search for a new facility location to four communities. The annual fixed costs and the variable costs are as follows:

Using break-even analysis, calculate the break-even quantities over the relevant ranges. If the expected demand is 20,000 units per year, what is the best location?

Community Fixed Costs per

Year Variable Costs per Unit

A $150,000 $62

B $300,000 $38

C $500,000 $24

D $600,000 $30

E

^XAMPLE

2

$62(20,000) = $1,240,000 $1,390,000

Commun

ity Fixed

Costs

Variable Costs (Cost per Unit)(No. of

Units)

Total Cost (Fixed + Variable)

A $150,000 B $300,000 C $500,000 D $600,000

$38(20,000) = $760,000 $1,060,000

$24(20,000) = $480,000 $980,000

$30(20,000) = $600,000 $1,200,000

A best B best C best

E

^XAMPLE

2

The figure shows the graph of the total cost lines.

| | | | | | | | | | | |

0 2 4 6 8 10 12 14 16 18 20 22 1,600 –

1,400 – 1,200 – 1,000 – 800 – 600 – 400 – 200 – –

Annual cost (thousands of dollars)

Q (thousands of units)

A

B C D

6.25 14.3

Break-even point

Break-even point

(20, 980) (20, 1,390)

(20, 1,200) (20, 1,060)

• A is best for low volumes

• B for intermediate volumes

• C for high volumes.

• We should no longer consider community D, because both its fixed and its variable costs are higher than community C’s.

Figure 13.3

E

XAMPLE

2

(A) (B)

$150,000 + $62Q = $300,000 + $38Q Q = 6,250 units

The break-even quantity between B and C lies at the end of the range over which B is best and the beginning of the final range where C is best.

(B) (C)

$300,000 + $38Q = $500,000 + $24Q Q = 14,286 units

The break-even quantity between A and B lies at the end of the first range, where A is best, and the beginning of the second range, where B is best.

E

^XAMPLE

2

No other break-even quantities are needed.

The break-even point between A and C lies above the shaded area, which does not mark either the start or the end of one of the three relevant ranges.

T

RANSPORTATION

M

^ODEL

 Finds amount to be shipped from several points of supply to several points of demand

 Solution will minimize total production and shipping costs

 A special class of linear

programming problems

G

EOGRAPHIC

I

NFORMATION

S

YSTEMS

(GIS)

 Important tool to help in location analysis

 Enables more complex demographic analysis

 Available data bases include

 Detailed census data

 Detailed maps

 Utilities

 Geographic features

 Locations of major services

G

EOGRAPHIC

I

NFORMATION

S

YSTEMS

(GIS)

L ^AYOUT P ^LANNING ?



Layout planning is

determining the best physical

arrangement of resources

within a facility

W

^{HY IS LAYOUT PLANNING IMPORTANT}

?



Eliminates unnecessary costs for space and materials handling



Reduces work-in-process inventory



Produces goods and services faster



Reduces distances that workers must travel in the workplace



Improves communication and morale



Increases retail sales



Improves brand image

T

^{YPES OF}

L

^AYOUTS

 Process layouts: Group similar resources together

 Product layouts: Designed to produce a specific product, or a small number of products efficiently

 Hybrid layouts: Combine aspects of both process and product layouts

 Fixed-Position layouts: Product is too large to move

 Examples: building construction, shipyard

 Resources must be brought to where they are needed

P

^{ROCESS AND}

P

^RODUCT

L

^AYOUTS