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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
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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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Eample of Capacity %e!irements
:Contin!ed;- Prod!ct from a Capacity
*ie,point
• '!estion-
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Eample of Capacity %e!irements
: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$hine re*'irement 1.50aor re*'irement 3.00
Family-size
er$ent $apa$ity 'sed 47.92
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$h. Cap. 240/000 aor 6
Small
er$ent $apa$ity 'sed 50.00
Ma$hine re*'irement 1.50
aor re*'irement 3.00Family-size
er$ent $apa$ity 'sed 47.92
Ma$hine re*'irement 0.96
aor re*'irement 2.88
1uestion2 (at are t(e values for columns !* 3 and 6 in t(e tale elo)51uestion2 (at are t(e values for columns !* 3 and 6 in t(e tale elo)5
56.67
1.70
3.40
58.33
1.17
3.50
66.67
2.00
4.00
70.83
1.42
4.25
80.00
2.40
4.80
83.33
1.67
5.00
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Eample of a Decision Tree Pro$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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Eample of a Decision Tree Pro$lem
:Contin!ed;- The Payoff Ta$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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Eample of a Decision Tree Pro$lem
: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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Eample of Decision Tree Pro$lem
:Contin!ed;- Step 23 Determine the
epected val!e of each decisionih demand +0.4,ih demand +0.4,
Medi'm demand +0.5,Medi'm demand +0.5,
ow demand +0.1,ow demand +0.1,
90 90
50 50
10 10
:;0.4+90,
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Eample of Decision Tree Pro$lem
: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
80.5
46
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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nd o( Chapter 10