ch10(strategic capacity planning)

8/18/2019 Ch10(Strategic Capacity Planning)

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©The McGraw-Hill Companies,


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Chapter 10

Strategic Capacity Planning


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• Strategic Capacity Planning Defined• Capacity Utilization & Best Operating

Level

• Economies & Diseconomies of Scale• The Eperience C!rve

• Capacity "oc!s# "lei$ility & Planning

• Determining Capacity %e!irements• Decision Trees

• Capacity Utilization & Service '!ality

OB(ECT)*ES


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Strategic Capacity Planning

Defined

• Capacity can $e defined as the a$ility to

hold# receive# store# or accommodate

• Strategic capacity planning is anapproach for determining the overall

capacity level of capital intensivereso!rces# incl!ding facilities# e!ipment#and overall la$or force size


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Capacity Utilization

• +here

• Capacity !sed –

rate of o!tp!t act!ally achieved• Best operating level

– capacity for ,hich the process ,as designed

leveloperatingBest

usedCapacityratenutilizatioCapacity =


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Best Operating Level

Eample- Engineers design engines and assem$ly lines to

operate at an ideal or .$est operating level/ to maimizeo!tp!t and minimize ,are

Eample- Engineers design engines and assem$ly lines to

operate at an ideal or .$est operating level/ to maimizeo!tp!t and minimize ,are

Underutilization

Best Operating

Level

Average

unit cost

of output

Volume

Overutilization


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Eample of Capacity Utilization

• D!ring one ,ee0 of prod!ction# a plantprod!ced 12 !nits of a prod!ct3 )ts historichighest or $est !tilization recorded ,as 456

!nits per ,ee03 +hat is this plant7s capacity!tilization rate8

• D!ring one ,ee0 of prod!ction# a plantprod!ced 12 !nits of a prod!ct3 )ts historichighest or $est !tilization recorded ,as 456

!nits per ,ee03 +hat is this plant7s capacity!tilization rate8

• Answer:

Capacity utilization rate = Capacity used . Best operating level

= 83/!" =".#$ or #$%

• Answer:

Capacity utilization rate = Capacity used . Best operating level

= 83/!" =".#$ or #$%


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Economies & Diseconomies of Scale

100-unitplant

200-unit

plant 300-unit

plant

400-unit

plant

Volume

Average

unit cost

of output

cono!ies o" #cale and t$e %perience Curve wor&ingcono!ies o" #cale and t$e %perience Curve wor&ing

'isecono!ies o" #cale start wor&ing'isecono!ies o" #cale start wor&ing


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The Eperience

C!rve As plants produce !ore products( t$ey

gain e%perience in t$e )est production

!et$ods and reduce t$eir costs per unit

As plants produce !ore products( t$ey

gain e%perience in t$e )est production

!et$ods and reduce t$eir costs per unit

&otal accumulated production of units

Cost or price

per unit

Yesterday

Today

Tomorrow


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Capacity "oc!s

• The concept of the focused factory holds

that prod!ction facilities ,or0 $est ,hen

they foc!s on a fairly limited set ofprod!ction o$9ectives

• Plants +ithin Plants :P+P; :fromS0inner; – Etend foc!s concept to operating level


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Capacity "lei$ility

• "lei$le plants

• "lei$le processes

• "lei$le ,or0ers


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Capacity Planning- Balance

#tage 1 #tage 2 #tage 3'nitsper

mont(*(000 +(000 ,(000

Un$alanced stages of prod!ctionUn$alanced stages of prod!ction

#tage 1 #tage 2 #tage 3'nitsper

mont(*(000 *(000 *(000

Balanced stages of prod!ctionBalanced stages of prod!ction

Maintainin !ystem "a#an$e% &'tp't o( one stae is thee)a$t inp't re*'irements (or the ne)t stae


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Capacity Planning

• "re!ency of Capacity


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Determining Capacity %e!irements

• 43 "orecast sales ,ithin each individ!alprod!ct line

• 53 Calc!late e!ipment and la$orre!irements to meet the forecasts

• 23 Pro9ect e!ipment and la$oravaila$ility over the planning horizon

1


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Eample of Capacity %e!irements

A manufacturer produces t)o lines of

mustard* +ancy+ine and ,eneric line. -ac( issold in small and familysize plastic ottles.

&(e follo)ing tale s(o)s forecast demand

for t(e ne0t four years.

Year% 1 2 3 4

FancyFine

!ma## +000s, 50 60 80 100

-ami#y +000s, 35 50 70 90Generic

!ma## +000s, 100 110 120 140

-ami#y +000s, 80 90 100 110

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:Contin!ed;- Prod!ct from a Capacity

*ie,point

• '!estion-


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:Contin!ed; - E!ipment and La$or

%e!irementsYear% 1 2 3 4

!ma## +000s, 150 170 200 240

-ami#y +000s, 115 140 170 200•Three 466#666 !nits>per>year machines are availa$le

for small>$ottle prod!ction3 T,o operators re!ired

per machine.

•T,o 456#666 !nits>per>year machines are availa$le

for family>sized>$ottle prod!ction3 Three operators

re!ired per machine3

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Year% 1 2 3 4

!ma## +000s, 150 170 200 240-ami#y +000s, 115 140 170 200

Small Ma$h. Cap. 300/000 aor 6

Family-size Ma$h. Cap. 240/000 aor 6

Small

er$ent $apa$ity 'sed 50.00

Ma$hine re*'irement 1.50aor re*'irement 3.00

Family-size


Ma$hine re*'irement 0.96

aor re*'irement 2.88

1uestion2 (at are t(e 4ear values for capacity* mac(ine*

and laor5

1uestion2 (at are t(e 4ear values for capacity* mac(ine*

and laor5

4?6#666@266#666A?6


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Year% 1 2 3 4

!ma## +000s, 150 170 200 240

-ami#y +000s, 115 140 170 200

Small Ma$h. Cap. 300/000 aor 6

Family-size Ma$h. Cap. 240/000 aor 6

Small



aor re*'irement 3.00Family-size



aor re*'irement 2.88

1uestion2 (at are t(e values for columns !* 3 and 6 in t(e tale elo)51uestion2 (at are t(e values for columns !* 3 and 6 in t(e tale elo)5

56.67

1.70

3.40

58.33

1.17

3.50

66.67

2.00

4.00

70.83

1.42

4.25

80.00

2.40

4.80

83.33

1.67

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©The McGraw-Hill Companies, Inc.,

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Eample of a Decision Tree Pro$lem

A glass factory specializing in crystal is e0periencing a

sustantial ac7log* and t(e firms management is

considering t(ree courses of action2

A9 Arrange for sucontractingB9 Construct ne) facilities

C9 :o not(ing ;no c(ange9

&(e correct c(oice depends largely upon demand* )(ic(

may e lo)* medium* or (ig(. By consensus* management

estimates t(e respective demand proailities as ".* ".


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:Contin!ed;- The Payoff Ta$le

0.1 0.5 0.4

ow Medi'm ih

10 50 90

" 120 25 200

C 20 40 60

&(e management also estimates t(e profits)(en c(oosing from t(e t(ree alternatives ;A*

B* and C9 under t(e differing proale levels of

demand. &(ese profits* in t(ousands of dollars

are presented in t(e tale elo)2

&(e management also estimates t(e profits)(en c(oosing from t(e t(ree alternatives ;A*

B* and C9 under t(e differing proale levels of

demand. &(ese profits* in t(ousands of dollars

are presented in t(e tale elo)2

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:Contin!ed;- Step 43 +e start $y dra,ing

the three decisions

"

C

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Eample of Decision Tree Pro$lem

:Contin!ed;- Step 53


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:Contin!ed;- Step 23 Determine the

epected val!e of each decisionih demand +0.4,ih demand +0.4,

Medi'm demand +0.5,Medi'm demand +0.5,

ow demand +0.1,ow demand +0.1,

90 90

50 50

10 10

:;0.4+90,


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:Contin!ed;- Step 3 a0e decisionih demand +0.4,

Medi'm demand +0.5,

ow demand +0.1,

ih demand +0.4,Medi'm demand +0.5,

ow demand +0.1,

"

Cih demand +0.4,

Medi'm demand +0.5,

ow demand +0.1,

90 50

10

200 25

120

60 40

20

62

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Alternative B generates t(e greatest e0pected profit* so

our c(oice is B or to construct a ne) facility

Alternative B generates t(e greatest e0pected profit* so

our c(oice is B or to construct a ne) facility

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Planning Service Capacity vs3

an!fact!ring Capacity

• Time- oods can not $e stored for later !se and

capacity m!st $e availa$le to provide a service

,hen it is needed

• Location- Service goods m!st $e at the

c!stomer demand point and capacity m!st $e

located near the c!stomer

• *olatility of Demand- !ch greater than in

man!fact!ring

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Capacity Utilization &

Service '!ality

• Best operating point is near F6 of capacity

• "rom F6 to 466 of service capacity# ,hat do

yo! thin0 happens to service !ality8

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ch10(strategic capacity planning)

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