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2006 Prentice Hall, Inc. 131
OperationsManagement
Chapter 13
Aggregate Planning
2006 Prentice Hall, Inc.
PowerPoint presentation to accompanyHeizer/RenderPrinciples of Operations Management, 6eOperations Management, 8e
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2006 Prentice Hall, Inc. 133
Learn ing Objec t ives
When you complete th is chapter , youshou ld be able to:
Desc r ibe or Exp lain:
How to do aggregate plann ing
How service f i rms develop
aggregate p lans
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2006 Prentice Hall, Inc. 134
Anheuser-Busch
Anheuser-Busch produces near ly 40% of
the beer consum ed in the U.S.
Matches f luctuat ing demand by brand to
plant, labor, and invento ry capacity toachieve high faci l i ty ut i l izat ion
High faci l i ty ut i l izat ion requ ires
Meticulous cleaning between batches Effect ive maintenance
Eff icient employees
Eff ic ient faci l i ty s chedul ing
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2006 Prentice Hall, Inc. 135
Aggregate Planning
Object ive is to m inim ize cost over theplann ing per iod by adjust ing
Produc t ion rates
Labo r levels
Inventory levels
Overtime work
Subcontract ing
Other contro l lable variables
Determ ine the quant i ty and t im ing o f
product ion for the immediate future
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Aggregate Planning
Quarter 1
Jan Feb Mar
150,000 120,000 110,000
Quarter 2
Apr May Jun
100,000 130,000 150,000
Quarter 3
Jul Aug Sep
180,000 150,000 140,000
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Masterproduc t i on
schedule andMRP
systems
Detailedwork
schedules
Processplanning and
capaci tydecis ions
Aggregateplan for
produc t i on
Aggregate Planning
Figure 13.2
Productdecis ions
Demandforecasts,orders
Marketplaceand
demand
Research
and
technology
Rawmaterialsavai lable
Externalcapacity
(subcont ractors)
Workforce
Inventoryon
hand
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Aggregate Planning
Combines appropr iate resou rces
into general terms
Part of a larger produc t ion p lann ingsystem
Disagg regat ion breaks the plan
down in to g reater detai l
Disagg regat ion resu l ts in a master
product ion schedule
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Aggregate Planning
Strategies1. Use inventor ies to absorb changes in
demand
2. Accommodate changes by vary ingwork force size
3. Use part-t imers, overt ime, or id le t ime to
abso rb changes
4. Use subcont rac tors and maintain a stab leworkforce
5. Change prices or other fac tors to
inf luence demand
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Capaci ty Opt ions
Changing invento ry levels
Inc rease invento ry in low demand
per iods to meet high demand in
the future
Inc reases costs asso ciated w ith
sto rage, insurance, handl ing,
obso lescence, and capital
investment
Shortages can mean lost sales due
to long lead t imes and poor
cus tomer serv ice
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Capaci ty Opt ions
Vary ing product ion rate through
overt ime or idle t ime
Al lows constant work force
May be dif f icu l t to meet large
increases in demand
Overt ime can be cost ly and may
dr ive down produc t iv i ty
Absorb ing id le t ime may be
di f f icul t
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Capaci ty Opt ions
Subcontract ing
Tempo rary measure du ring
per iods o f peak demand
May be cost ly
Assur ing qual ity and t imely
del ivery may be di f f icu l t
Exposes your customers to apos s ib le competi tor
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Demand Opt ions
In f luenc ing demand
Use advert is ing o r promot ion to
increase demand in low per iods
Attempt to shi f t demand to s low
per iods
May no t be su f fic ient to balance
demand and capaci ty
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2006 Prentice Hall, Inc. 1318
Demand Opt ions
Back order ing du r ing high -
demand per iods
Requ ires cu stom ers to wait for an
order w i thou t loss of goodw i ll orthe order
Mos t effect ive when there are few
i f any subst i tutes for the product
or serv ice
Often resul ts in lost sales
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Aggregate Plann ing Opt ions
Table 13.1
Opt ion Adv antages Disadvantages Some Comm ents
Changing
inventory
levels
Changes in
human
resourc es are
gradual or
non e; no abruptproduct ion
changes
Inventory
ho ld ing cost
may in crease.
Shor tages m ay
resul t in lo stsales.
App l ies main ly to
produ ct ion, not
service,
operat ions
Varying
workforce
size byh i r ing or
layoffs
Avo ids the costs
of oth er
alternatives
Hir ing , layo ff,
and tra in ing
costs m ay besigni f icant
Used where size
of labor po ol is
large
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Aggregate Plann ing Opt ions
Table 13.1
Opt ion Adv antages Disadvantages Some Comm ents
Varying
product ion
rates
through
over t ime oridle t ime
Matches
seasonal
f luctuat ions
wi tho ut hir ing/
t rain ing cos ts
Overt ime
premiums; t i red
wo rkers; may
not meet
demand
Al low s f lex ib i l ity
wi th in the
aggregate plan
Sub-
contract ing
Permits
f lexibi l i ty and
smo oth ing of
the f irms
output
Los s of qual i ty
contro l ;
reduc ed prof i ts ;
loss o f futurebus iness
App l ies main ly in
product ion
set t ings
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Aggregate Plann ing Opt ions
Table 13.1
Opt ion Adv antages Disadvantages Some Comm ents
Using par t-
t ime
workers
Is less cost ly
and mo re
f lexible than
ful l - t ime
workers
High turno ver/
t rain ing c osts;
qual i ty su ffers;
schedu l ing
dif f icul t
Good for
uns ki l led jobs in
areas w ith large
temp orary labor
poo ls
Inf luencing
demand
Tries to u se
excess
capacity.
Discounts draw
new cus tomers.
Uncertainty in
demand. Hard
to match
demand to
sup ply exact ly.
Creates
market ing
ideas.
Overbooking
used in somebusinesses.
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Aggregate Plann ing Opt ions
Table 13.1
Opt ion Adv antages Disadvantages Some Comm ents
Back
order ing
dur ing
h igh-
demandper iods
May avoid
overt ime.
Keeps capacity
constant.
Customer must
be wi l l ing to
wait , but
goo dw i l l is lost .
Al low s f lex ib i l ity
wi th in the
aggregate plan
Counter-
seasonal
product
and servicemix ing
Ful ly u t i l izes
resources;
al lows stable
workforce
May require
ski l ls or
equipment
outs ide thef irms areas o f
expert ise
Risky find ing
products or
serv ices w ith
opposi tedemand
patterns
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2006 Prentice Hall, Inc. 1324
Methods for Agg regatePlanning
A m ixed s trategy m ay be the best
way to achieve m in imum costs
There are many poss ible m ixed
strategies
Finding the opt imal plan is no t
always possib le
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Mixing Opt ions toDevelop a Plan
Chase strategy
Match output rates to demand
forecast for each period
Vary work force levels o r vary
product ion rate
Favo red by many serv iceorganizat ions
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Mixing Opt ions toDevelop a Plan
Level strategy
Dai ly product ion is un i form
Use inventory or id le t ime as bu f fer
Stable product ion leads to bet ter
qual ity and product iv i ty
Some com bination o f capaci tyop t ions, a mixed strategy, m igh t be
the best so lut ion
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Graph ical and Chart ingMethods
Popu lar techniques
Easy to understand and use
Trial-and -error app roaches that do
no t guarantee an op t imal so lut ion
Requ ire on ly l im i ted compu tat ions
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Graph ical and Chart ingMethods
1. Determine the demand for each period
2. Determ ine the capaci ty for regu lar t ime,
overt ime, and subcontract ing each period
3. Find labor costs , h i r ing and layof f costs ,
and inventory ho ld ing costs
4. Cons ider company po l icy on workers andstoc k levels
5. Develop alternative plans and exam ine
their total costs
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Planning Example 1
Table 13.2
Month Expected DemandProduct ion
DaysDemand Per Day
(computed)
Jan 900 22 41
Feb 700 18 39
Mar 800 21 38
Apr 1,200 21 57
May 1,500 22 68
June 1,100 20 55
6,200 124
= = 50uni ts p er day6,200
124
Averagerequirement
=Total expected demand
Number of product ion days
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Planning Example 1
Figure 13.3
70
60
50
40
30
0 Jan Feb Mar Ap r May Jun e = Mon th
22 18 21 21 22 20 = Num ber of
work ing days
Pro
duc
tionra
tep
erwork
ing
day
Level produ ct ion u sing averagemonth ly forecast demand
Forecast demand
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Planning Example 1
Table 13.3
Cost Information
Inventory carry cos t $ 5per uni t per mon th
Subcon tract ing co st per uni t $10per uni t
Av erage p ay rate $ 5per hour ($40per day)
Overt ime p ay rate $ 7per hour(above 8hou rs per day)
Labor-hou rs to produ ce a uni t 1.6hou rs per un i t
Cost of in creasing dai ly p rodu ct ion rate
(hir ing and training )
$300per uni t
Cost of d ecreasing dai ly prod uct ion rate(layoffs)
$600per uni t
Month
Product ion at
50Units p er DayDemand
Forecast
Month lyInventory
Change
Ending
Inventory
Jan 1,100 900 +200 200
Feb 900 700 +200 400
Mar 1,050 800 +250 650Apr 1,050 1,200 -150 500
May 1,100 1,500 -400 100
June 1,000 1,100 -100 0
1,850
Total units of inv entory carr ied over from one
month to the next = 1,850uni ts
Workforce required to produc e 50uni ts per day = 10workers
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Planning Example 1
Table 13.3
Cost Information
Inventory carry cos t $ 5per uni t per mon th
Subcon tract ing co st per uni t $10per uni t
Av erage p ay rate $ 5per hour ($40per day)
Overt ime p ay rate $ 7per hour(above 8hou rs per day)
Labor-hou rs to produ ce a uni t 1.6hou rs per un i t
Cost of in creasing dai ly p rodu ct ion rate
(hir ing and training )
$300per uni t
Cost of d ecreasing dai ly prod uct ion rate(layoffs)
$600per uni t
Month
Product ion at
50Units p er DayDemand
Forecast
Month lyInventory
Change
Ending
Inventory
Jan 1,100 900 +200 200
Feb 900 700 +200 400
Mar 1,050 800 +250 650Apr 1,050 1,200 -150 500
May 1,100 1,500 -400 100
June 1,000 1,100 -100 0
1,850
Total units of inv entory carr ied over from one
month to the next = 1,850uni ts
Workforce required to produc e 50uni ts per day = 10workers
Costs Calculat ions
Invento ry carrying $9,250 (= 1,850units carr ied x $5per uni t)
Regular-t ime labo r 49,600 (= 10workers x $40per
day x 124days)Other cos ts (overt ime,
hir in g, layoffs ,
subcontract ing) 0
Total cos t $58,850
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Planning Example 1
Figure 13.4
Cumu
lative
dem
an
dun
its
7,000
6,000
5,000
4,000
3,000
2,000
1,000
Jan Feb Mar Ap r May June
Cumu lative forecastrequirements
Cumulat ive levelproduct ion us ing
average mon thlyforecast
requirements
Reduct ionof inventory
Excess inventory
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Planning Example 2
Table 13.2
Month Expected DemandProduct ion
DaysDemand Per Day
(computed)
Jan 900 22 41
Feb 700 18 39
Mar 800 21 38
Apr 1,200 21 57
May 1,500 22 68
June 1,100 20 55
6,200 124
Minimum requirement= 38un i ts per day
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Planning Example 2
70
60
50
40
30
0 Jan Feb Mar Ap r May Jun e = Mon th
22 18 21 21 22 20 = Num ber of
work ing days
Pro
duc
tionra
tep
erwork
ing
day
Level prod uct ionus ing low est
mo nthly forecast
demand
Forecast demand
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Planning Example 2
Table 13.3
Cost Information
Inventory c arry ing cost $ 5per uni t per mon th
Subcon tract ing co st per uni t $10per uni t
Av erage p ay rate $ 5per hour ($40per day)
Overt ime p ay rate $ 7per hour(above 8hou rs per day)
Labor-hou rs to produ ce a uni t 1.6hou rs per un i t
Cost of in creasing dai ly p rodu ct ion rate
(hir ing and training )
$300per uni t
Cost of d ecreasing dai ly prod uct ion rate(layoffs)
$600per uni t
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Planning Example 3
Table 13.2
Month Expected DemandProduct ion
DaysDemand Per Day
(computed)
Jan 900 22 41
Feb 700 18 39
Mar 800 21 38
Apr 1,200 21 57May 1,500 22 68
June 1,100 20 55
6,200 124
Produc t ion = Expected Demand
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Planning Example 3
70
60
50
40
30
0 Jan Feb Mar Ap r May Jun e = Mon th
22 18 21 21 22 20 = Num ber of
work ing days
Pro
duc
tionra
tep
erwork
ing
day
Forecast demand and
month ly product ion
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Planning Example 3
Table 13.3
Cost Information
Inventory c arry ing cost $ 5per uni t per mon th
Subcon tract ing co st per uni t $10per uni t
Av erage p ay rate $ 5per hour ($40per day)
Overt ime p ay rate $ 7per hour(above 8hou rs per day)
Labor-hou rs to produ ce a uni t 1.6hou rs per un i t
Cost of in creasing dai ly p rodu ct ion rate
(hir ing and training )
$300per uni t
Cost of d ecreasing dai ly prod uct ion rate(layoffs)
$600per uni t
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Planning Example 3
Table 13.3
Cost Information
Inventory c arry ing cost $ 5per uni t per mon th
Subcon tract ing co st per uni t $10per uni t
Av erage p ay rate $ 5per hour ($40per day)
Overt ime p ay rate $ 7per hour(above 8hou rs per day)
Labor-hou rs to produ ce a uni t 1.6hou rs per un i t
Cost of in creasing dai ly p rodu ct ion rate
(hir ing and training )
$300per uni t
Cost of d ecreasing dai ly prod uct ion rate(layoffs)
$600per uni t
Month
Forecast
(un i ts)
Daily
Prod
Rate
BasicProduct ion
Cost
(demand x1.6hrs/unit x
$5/h r)
Extra Cost of
Increasing
Product ion
(h ir ing cost)
Extra Cost of
Decreasing
Product ion
(layof f cost) Total Cost
Jan 900 41 $ 7,200 $ 7,200
Feb 700 39 5,600 $1,200(= 2 x $600)6,800
Mar 800 38 6,400 $600
(= 1 x $600)7,000
Apr 1,200 57 9,600$5,700
(= 19 x $300) 15,300
May 1,500 68 12,000 $3,300(= 11 x $300) 15,300
June 1,100 55 8,800 $7,800
(= 13 x $600)16,600
$49,600 $9,000 $9,600 $68,200
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Comparison of Three Plans
Table 13.5
Cos t Plan 1 Plan 2 Plan 3
Invento ry carrying $ 9,250 $ 0 $ 0
Regular labor 49,600 37,696 49,600
Overt ime labor 0 0 0
Hir ing 0 0 9,000
Layof fs 0 0 9,600
Subcontract ing 0 14,880 0Total cos t $58,850 $52,576 $68,200
Plan 2 is the lowest cost op t ion
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Mathemat ical App roaches
Useful for generat ing strateg ies
Transpo rtat ion Method of L inear
Programming
Produces an opt im al plan
Management Coeff ic ients Model
Model bui l t around managers
experience and performance
Other Models
Linear Decis ion Rule
Simulat ion
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Transpo rtat ion Method
Sales PeriodMar Ap r May
Demand 800 1,000 750Capacity:
Regular 700 700 700Overt ime 50 50 50Subcontract ing 150 150 130
Beginning inventory 100 tires
CostsRegu lar t im e $40 per tireOvert ime $50per tireSubcontract ing $70 per tireCarrying $ 2 per tire Table 13.6
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Transpo rtat ion Example
Impo rtant po ints
1. Car rying cos ts are $2/t ire/m onth . Ifgoods are made in one per iod and held
over to the next , ho lding costs areincurred
2. Supp ly must equal demand, so a
dummy column cal led unused
capacityis added
3. Because back ordering is not v iab le in
this examp le, cel ls that m igh t be used to
sat isfy earl ier demand are no t available
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Transpo rtat ion Example
Impo rtant po ints
4. Quant it ies in each column des ignate the
levels of invento ry needed to meet
demand requ i rements5. In general , produc t ion should be
allocated to the lowest cos t cel l
avai lable withou t exceeding unused
capaci ty in the row or demand in theco lumn
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Management Coeff ic ien tsModel
Bui lds a model based on
managers exper ience and
performance
A regression model is constructed
to def ine the relat ionsh ips between
decis ion var iables
Object ive is to remove
incons is tenc ies in decis ion making
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Other Models
Linear Decis ion Rule
Minim izes cos ts using quadrat ic cost cu rves
Operates over a part icu lar t ime period
Simulat ion
Uses a search pro cedu re to try d if ferent
com binat ions of var iables Develops feasib le but not necessar i ly opt imal
so lu t ions
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Summary o f AggregatePlann ing Methods
Techniques
Solut ion
App roaches Imp or tant Asp ects
Graphical/chart ing
methods
Tr ial and error Simp le to un derstand and
easy to us e. Many solut ion s;
one chosen may not beopt imal.
Transportat ion
method of l inear
programming
Optim izat ion LP softw are avai lable; permits
sensi t iv i ty analys is and new
con straints; l inear funct ion s
may not be real ist ic
Management
coef fic ients mo del
Heur ist ic Simp le, easy to implement;
t r ies to m imic m anagers
decis ion process; uses
regression
Table 13.8
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Five Serv ice Scenarios
Restaurants
Smooth ing the product ion
process
Determ ining the wo rkforc e size
Hospi ta ls
Responding to pat ient demand
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Five Serv ice Scenarios
A ir line industry
Extremely complex plann ing
problem
Involves number of f l igh ts,
number of passengers, air and
ground personnel
Resou rces spread through the
ent i re system