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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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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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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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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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8/56 2006 Prentice Hall, Inc. 138

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



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



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



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



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



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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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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Table 13.1


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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Table 13.1


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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Table 13.1


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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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







$300per uni t


$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


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


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







$300per uni t


$600per uni t


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Planning Example 3

Table 13.2


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


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








$300per uni t


$600per uni t


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Planning Example 3

Table 13.3

Cost Information








$300per uni t


$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

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