Aggregate Planning. Planning Horizon Aggregate planning: Intermediate-range capacity planning,...

Aggregate Planning

Planning Horizon

Aggregate planning: Intermediate-range capacity planning, usually covering 6 to 18 months.

Shortrange

Intermediate range

Long range

Now 6 months 18 months

©The McGraw-Hill Companies, Inc., 2004

3

Master scheduling

Material requirements planning

Order schedulingWeekly workforce andcustomer scheduling

Daily workforce and customer scheduling

Process planning

Strategic capacity planning

Sales and operations (aggregate) planning

Longrange

Intermediaterange

Shortrange

ManufacturingServices

Sales plan Aggregate operations plan

Forecasting & demand management

Operations Planning Activities

• Long-range planning– Greater than one year planning horizon– Usually performed in annual increments

• Medium-range planning– Six to eighteen months – Usually with monthly or quarterly increments

• Short-range planning– One day to less than six months– Usually with weekly increments

Planning Tasks and Responsibilities

Aggregate Production Planning (APP)

Matches market demand to company resources Plans production 6 months to 18 months in

advance Expresses demand, resources, and capacity in

general terms Develops a strategy for economically meeting

demand Establishes a company-wide game plan for

allocating resources

Balancing Aggregate Demandand Aggregate Production Capacity

0

2000

4000

6000

8000

10000

Jan Feb Mar Apr May Jun

45005500

7000

10000

8000

6000

0

2000

4000

6000

8000

10000


9000 90009900

88009500 9500

Suppose the figure to the right represents forecast demand in units

Suppose the figure to the right represents forecast demand in units

Now suppose this lower figure represents the aggregate capacity of the company to meet demand

Now suppose this lower figure represents the aggregate capacity of the company to meet demand

What we want to do is balance out the production rate, workforce levels, and inventory to make these figures match up

What we want to do is balance out the production rate, workforce levels, and inventory to make these figures match up

Aggregate Plan: Relationships

AggregatePlan for

Production

DemandForecasts,

orders

MasterProduction

Schedule, and MRP systems

Detailed WorkSchedules

ExternalCapacity

Subcontractors

Inventory OnHand

Raw MaterialsAvailable

Work Force

Marketplaceand Demand

Research andTechnology

ProductDecisions

ProcessPlanning & Capacity

Decisions

Inputs and Outputs to APP

CompanyPolicies

CompanyPolicies

StrategicObjectivesStrategic

ObjectivesCapacity

ConstraintsCapacity

Constraints

Units or dollarssubcontracted,

backordered, or lost

Units or dollarssubcontracted,

backordered, or lost

Size ofWorkforce

Size ofWorkforce

Productionper month

(in units or $)

Productionper month

(in units or $)

InventoryLevels

InventoryLevels

FinancialConstraintsFinancial

ConstraintsDemand

ForecastsDemand

Forecasts

AggregateProductionPlanning

AggregateProductionPlanning

Resources• Workforce• Facilities

Demand forecastPolicies

• Subcontracting• Overtime• Inventory levels• Back orders

Common unit for measuring outputs

Costs• Inventory carrying• Back orders• Hiring/firing• Overtime• Inventory changes• Subcontracting

Aggregate Planning Inputs

Aggregate Planning Outputs

• A plan that specifies the optimal combination of– production rate (units completed per unit of

time)– workforce level (number of workers)– inventory on hand (inventory carried from

previous period– Subcontracting levels (if any)– Backordering levels (if any)

• Meet demand

• Use capacity efficiently

• Meet inventory policy

• Minimize total cost

Aggregate Planning Goals

Aggregate Planning Strategies

• Proactive

– Alter demand to match capacity

• Reactive

– Alter capacity to match demand

• Mixed

– Some of each

Demand Management Shifting demand into other periods by

incentives, promotions, advertising campaigns, pricing, etc.

Offering product or services with counterseasonal demand patterns (counterseasonal product mixing)

Backordering Creation of new demand Partnering with suppliers to reduce information

distortion along the supply chain

Producing at a constant rate and using inventories to absorb fluctuations in demand ie. changing inventory levels

Varying work force size (hiring and firing workers) so that production matches demand

Varying production capacity by increasing or decreasing working hours (overtime or idle time)

Options of Adjusting Capacity to Meet Demand (1 of 2)

Using part-time workers to change production rateSubcontracting work to other firmsProviding the service or product at a later time

period (backordering)

Options of Adjusting Capacity to Meet Demand (2 of 2)

Strategy Details

Overtime & undertime - common when demand fluctuations are not extreme

Subcontracting - useful if supplier meets quality & time requirements

Part-time workers - feasible for unskilled jobs or if labor pool exists

Backordering - only works if customer is willing to wait for product/services

Capacity Options - Advantages and Disadvantages (1 of 4)

Option Advantage Disadvantage SomeComments

Changinginventory levels

Changes inhuman resourcesare gradual, notabruptproductionchanges

Inventoryholding costs;Shortages mayresult in lostsales

Applies mainlyto production,not service,operations

Varyingworkforce sizeby hiring orlayoffs

Avoids use ofother alternatives

Hiring, layoff,and trainingcosts

Used where sizeof labor pool islarge


Varyingproduction ratesthrough overtimeor idle time

Matches seasonalfluctuationswithouthiring/trainingcosts

Overtimepremiums, tiredworkers, may notmeet demand

Allowsflexibility withinthe aggregateplan

Subcontracting Permitsflexibility andsmoothing of thefirm's output

Loss of qualitycontrol; reducedprofits; loss offuture business

Applies mainlyin productionsettings

Advantages/Disadvantages (2 of 4)



Using part-timeworkers

Less costly andmore flexiblethan full-timeworkers

Highturnover/trainingcosts; qualitysuffers;schedulingdifficult

Good forunskilled jobs inareas with largetemporary laborpools

Influencingdemand

Tries to useexcess capacity.Discounts drawnew customers.

Uncertainty indemand. Hard tomatch demand tosupply exactly.

Createsmarketing ideas.Overbookingused in somebusinesses.



Back orderingduring high-demand periods

May avoidovertime. Keepscapacity constant

Customer mustbe willing towait, butgoodwill is lost.

Many companiesbackorder.

Counterseasonalproducts andservice mixing

Fully utilizesresources; allowsstable workforce.

May requireskills orequipmentoutside a firm'sareas ofexpertise.

Risky findingproducts orservices withopposite demandpatterns.

The Extremes

Level Strategy

Chase Strategy

Production equals

demand

Production rate is constant

Basic Aggregate Planning Strategies for Meeting Demand

Level capacity strategy:

• Keeping work force constant and maintaining a steady rate of regular-time output while meeting variations in demand by a combination of options (such as using inventories + subcontracting)

Chase demand strategy:

• Changing workforce levels so that production matches demand (the planned output for a period is set at the expected demand for that period.)

Maintaining resources for high demand levels • Ensures high levels of customer service

Level Production

Production

Demand

Un

its

Un

its

TimeTime

Chase Demand

Production

Demand

Un

its

Time

Level Strategy: Forecast and Average Forecast Demand

0

10

20

30

40

50

60

70

Pro

duction r

ate

per

work

ing d

ay


Forecast Demand

Level production using average monthly forecast demand

22 18 21 21 22 20

Level Strategy: Cumulative Demand Graph


Cumulative forecast requirements

Cumulative level production using average monthly

forecast requirements

Reduction of inventory

Excess inventoryCum

ulat

ive D

eman

d (U

nits

)7,000

6,000

5,000

4,000

3,000

2,000

1,000

Level Approach

• Advantages

– Stable output rates and workforce

• Disadvantages

– Greater inventory costs

– Increased overtime and idle time

– Resource utilizations vary over time

Chase Approach

• Advantages

– Investment in inventory is low

– Labor utilization in high

• Disadvantages

– The cost of adjusting output rates and/or workforce levels

Graphical & charting techniques• Popular & easy-to-understand• Trial & error approach

Mathematical approaches• Linear programming • Transportation method • Linear decision rule (LDR)• Search decision rule (SDR)• Management coefficients model• Simulation

Aggregate Planning Methods

Summary of Planning TechniquesTechnique Solution Characteristics

Graphical/charting Trial and error

Intuitively appealing, easy to understand; solution not necessarily optimal.

Linear programming

Optimizing Computerized; linear assumptions not always valid.

Linear decision rule

Optimizing Complex, requires considerable effort to obtain pertinent cost information and to construct model; cost assumptions not always valid.

Simulation Trial and error

Computerized models can be examined under a variety of conditions.

1. Forecast demand for each period

2. Determine capacities (for regular time, overtime, subcontracting) for each period

3. Identify policies that are pertinent

4. Determine costs (labor, hiring/firing, holding etc.)

5. Develop alternative plans and costs

6. Select the best plan that satisfies objectives. Otherwise return to step 5.

Steps of Trial & Error Method

Aggregate Planning Using Pure Strategies

(Example 1)

Hiring cost = $100 per worker

Firing cost = $500 per worker

Inventory carrying cost = $0.50 pound per quarter

Production per employee = 1,000 pounds per quarter

Beginning work force = 100 workers

QUARTER SALES FORECAST (LB)

Spring 80,000Summer 50,000Fall 120,000Winter 150,000

Level Production Strategy(1 of 2)

QUARTER SALES FORECAST (LB)

Spring 80,000Summer 50,000Fall 120,000Winter 150,000

Level production

= 100,000 pounds

(50,000 + 120,000 + 150,000 + 80,000)4

Level Production Strategy(2 of 2)

Spring 80,000 100,000 20,000Summer 50,000 100,000 70,000Fall 120,000 100,000 50,000Winter 150,000 100,000 0

Total 400,000 140,000

Cost = 140,000 pounds x 0.50 per pound = $70,000

SALES PRODUCTIONQUARTER FORECAST PLAN INVENTORY

Spring 80,000 80,000 80 0 20Summer 50,000 50,000 50 0 30Fall 120,000 120,000 120 70 0Winter 150,000 150,000 150 30 0

100 50

SALES PRODUCTION WORKERS WORKERS WORKERSQUARTER FORECAST PLAN NEEDED HIRED FIRED

Cost = (100 workers hired x $100) + (50 workers fired x $500)

= $10,000 + 25,000 = $35,000

Chase Demand Strategy

APP Using Mixed Strategies

Production per employee = 100 cases per monthWage rate = $10 per case for regular production

= $15 per case for overtime= $25 for subcontracting

Hiring cost = $1000 per workerFiring cost = $500 per worker

Inventory carrying cost = $1.00 case per monthBeginning work force = 10 workers

January 1000 July 500February 400 August 500March 400 September 1000April 400 October 1500May 400 November 2500June 400 December 3000

MONTH DEMAND (CASES) MONTH DEMAND (CASES)

Aggregate Planning(Example 2)

Materials $5/unitHolding costs $1/unit per mo.Marginal cost of stockout $1.25/unit per mo.Hiring and training cost $200/workerLayoff costs $250/workerLabor hours required 0.15 hrs/unitStraight time labor cost $8/hourBeginning inventory 250 unitsProductive hours/worker/day 7.25Paid straight hrs/day 8

Suppose we have the following unit demand and cost information:

Suppose we have the following unit demand and cost information:

Demand/mo Jan Feb Mar Apr May Jun

4500 5500 7000 10000 8000 6000

Jan Feb Mar Apr May JunDays/mo 22 19 21 21 22 20Hrs/worker/mo 159.5 137.75 152.25 152.25 159.5 145Units/worker 1063.33 918.33 1015 1015 1063.33 966.67$/worker $1,408 1,216 1,344 1,344 1,408 1,280

Demand/mo Jan Feb Mar Apr May Jun

4500 5500 7000 10000 8000 6000

Given the demand and cost information below, whatare the aggregate hours/worker/month, units/worker, and dollars/worker?

Given the demand and cost information below, whatare the aggregate hours/worker/month, units/worker, and dollars/worker?

7.25x22

7.25/0.15=48.33 & 48.33x22=1063.3322x8hrsx$8=$1408

Cut-and-Try Example: Determining Straight Labor Costs and Output

Chase Strategy(Hiring & Firing to meet demand)

JanDays/mo 22Hrs/worker/mo 159.5Units/worker 1,063.33$/worker $1,408

JanDemand 4,500Beg. inv. 250Net req. 4,250Req. workers 3.997HiredFired 3Workforce 4Ending inventory 0

Lets assume our current workforce is 7 workers.

Lets assume our current workforce is 7 workers.

First, calculate net requirements for production, or 4500-250=4250 units

Then, calculate number of workers needed to produce the net requirements, or 4250/1063.33=3.997 or 4 workers

Finally, determine the number of workers to hire/fire. In this case we only need 4 workers, we have 7, so 3 can be fired.

Jan Feb Mar Apr May JunDays/mo 22 19 21 21 22 20Hrs/worker/mo 159.5 137.75 152.25 152.25 159.5 145Units/worker 1,063 918 1,015 1,015 1,063 967$/worker $1,408 1,216 1,344 1,344 1,408 1,280

Jan Feb Mar Apr May JunDemand 4,500 5,500 7,000 10,000 8,000 6,000Beg. inv. 250Net req. 4,250 5,500 7,000 10,000 8,000 6,000Req. workers 3.997 5.989 6.897 9.852 7.524 6.207Hired 2 1 3Fired 3 2 1Workforce 4 6 7 10 8 7Ending inventory 0 0 0 0 0 0

Below are the complete calculations for the remaining months in the six month planning horizon


Jan Feb Mar Apr May JunDemand 4,500 5,500 7,000 10,000 8,000 6,000Beg. inv. 250Net req. 4,250 5,500 7,000 10,000 8,000 6,000Req. workers 3.997 5.989 6.897 9.852 7.524 6.207Hired 2 1 3Fired 3 2 1Workforce 4 6 7 10 8 7Ending inventory 0 0 0 0 0 0

Jan Feb Mar Apr May Jun CostsMaterial $21,250.00 $27,500.00 $35,000.00 $50,000.00 $40,000.00 $30,000.00 203,750.00Labor 5,627.59 7,282.76 9,268.97 13,241.38 10,593.10 7,944.83 53,958.62Hiring cost 400.00 200.00 600.00 1,200.00Firing cost 750.00 500.00 250.00 1,500.00

$260,408.62

Below are the complete calculations for the remaining months in the six month planning horizon with the other costs included

Level Workforce Strategy (Surplus and Shortage Allowed)

JanDemand 4,500Beg. inv. 250Net req. 4,250Workers 6Production 6,380Ending inventory 2,130Surplus 2,130Shortage

Lets take the same problem as before but this time use the Level Workforce strategy

Lets take the same problem as before but this time use the Level Workforce strategy

This time we will seek to use a workforce level of 6 workers

This time we will seek to use a workforce level of 6 workers

Jan Feb Mar Apr May JunDemand 4,500 5,500 7,000 10,000 8,000 6,000Beg. inv. 250 2,130 2,140 1,230 -2,680 -1,300Net req. 4,250 3,370 4,860 8,770 10,680 7,300Workers 6 6 6 6 6 6Production 6,380 5,510 6,090 6,090 6,380 5,800Ending inventory 2,130 2,140 1,230 -2,680 -1,300 -1,500Surplus 2,130 2,140 1,230Shortage 2,680 1,300 1,500

Note, if we recalculate this sheet with 7 workers we would have a surplus

Note, if we recalculate this sheet with 7 workers we would have a surplus



Jan Feb Mar Apr May Jun4,500 5,500 7,000 10,000 8,000 6,000

250 2,130 10 -910 -3,910 -1,6204,250 3,370 4,860 8,770 10,680 7,300

6 6 6 6 6 66,380 5,510 6,090 6,090 6,380 5,8002,130 2,140 1,230 -2,680 -1,300 -1,5002,130 2,140 1,230

2,680 1,300 1,500

Jan Feb Mar Apr May Jun$8,448 $7,296 $8,064 $8,064 $8,448 $7,680 $48,000.0031,900 27,550 30,450 30,450 31,900 29,000 181,250.002,130 2,140 1,230 5,500.00

3,350 1,625 1,875 6,850.00

$241,600.00



Note, total costs under this strategy are less than Chase at $260.408.62

Note, total costs under this strategy are less than Chase at $260.408.62

LaborMaterialStorageStockout

APP by Linear Programming

whereHt = # hired for period tFt = # fired for period tIt = inventory at end

of period tPt = units produced

in period tWt = workforce size

for period t

Minimize Z = $100 (H1 + H2 + H3 + H4)

+ $500 (F1 + F2 + F3 + F4)

+ $0.50 (I1 + I2 + I3 + I4)

Subject to

P1 - I1 = 80,000 (1)

Demand I1 + P2 - I2 = 50,000 (2)

constraints I2 + P3 - I3 = 120,000 (3)

I3 + P4 - I4 = 150,000 (4)

Production 1000 W1 = P1 (5)

constraints 1000 W2 = P2 (6)

1000 W3 = P3 (7)

1000 W4 = P4 (8)

100 + H1 - F1 = W1 (9)

Work force W1 + H2 - F2 = W2 (10)

constraints W2 + H3 - F3 = W3 (11)

W3 + H4 - F4 = W4 (12)

APP by the Transportation Method

1 900 1000 100 5002 1500 1200 150 5003 1600 1300 200 5004 3000 1300 200 500

Regular production cost per unit $20Overtime production cost per unit $25Subcontracting cost per unit $28Inventory holding cost per unit per period $3Beginning inventory 300 units

EXPECTED REGULAR OVERTIME SUBCONTRACTQUARTER DEMAND CAPACITY CAPACITY CAPACITY

The Transportation Tableau

UnusedPERIOD OF PRODUCTION 1 2 3 4 Capacity Capacity

Beginning 0 3 6 9

Inventory 300 — — — 300

Regular 600 300 100 — 1000

Overtime 100 100

Subcontract 500

Regular 1200 — — 1200

Overtime 150 150

Subcontract 250 250 500

Regular 1300 — 1300

Overtime 200 — 200

Subcontract 500 500

Regular 1300 1300

Overtime 200 200

Subcontract 500 500

Demand 900 1500 1600 3000 250

1

2

3

4

PERIOD OF USE

20 23 26 29

25 28 31 34

28 31 34 37

20 23 26

25 28 31

28 31 34

20 23

25 28

28 31

20

25

28


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Burruss’ Production Plan

11 900900 10001000 100100 00 50050022 15001500 12001200 150150 250250 60060033 16001600 13001300 200200 500500 1000100044 30003000 13001300 200200 500500 00

TotalTotal 70007000 48004800 650650 12501250 21002100

REGULARREGULAR SUB-SUB- ENDINGENDINGPERIODPERIOD DEMANDDEMAND PRODUCTIONPRODUCTION OVERTIMEOVERTIME CONTRACTCONTRACT INVENTORYINVENTORY


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Other Quantitative Techniques

Linear decision rule (LDR)Linear decision rule (LDR)

Search decision rule (SDR)Search decision rule (SDR)

Management coefficients modelManagement coefficients model

Hierarchical Planning ProcessItems

Product lines or families

Individual products

Components

Manufacturing operations

Resource Level

Plants

Individual machines

Critical work

centers

Production Planning

Capacity Planning

Resource requirements

plan

Rough-cut capacity

plan

Capacity requirements

plan

Input/ output control

Aggregate production

plan

Master production schedule

Material requirements

plan

Shop floor

schedule

All work

centers

Aggregate Plan to Master Schedule

AggregatePlanning

Disaggregation

MasterSchedule

• Master schedule: The result of disaggregating an aggregate plan; shows quantity and timing of specific end items needed to meet demand for a scheduled horizon.

• Rough-cut capacity planning: Approximate balancing of capacity and demand to test the feasibility of a master schedule.

Disaggregating the Aggregate Plan


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Master Scheduling Process

MasterScheduling

Beginning inventory

Forecast

Customer orders

Inputs Outputs

Projected inventory

Master production schedule

Uncommitted inventory

Figure 13.6


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Projected On-hand Inventory

Projected on-handinventory

Inventory fromprevious week

Current week’srequirements

-=


57

Projected On-hand InventoryProjected On-hand Inventory

64 1 2 3 4 5 6 7 8Forecast 30 30 30 30 40 40 40 40

Customer Orders (committed) 33 20 10 4 2

Projected on-hand inventory 31 1 -29

JUNE JULY

Beginning Inventory

Customer orders are larger than forecast in week 1

Forecast is larger than Customer orders in week 2

Forecast is larger than Customer orders in week 3

Figure 13.8


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Time Fences

Time Fences – points in timethat separate phases of a master schedule planninghorizon.


59

Time Fences in MPSTime Fences in MPS

Period

“frozen”(firm orfixed)

“slushy”somewhat

firm

“liquid”(open)

Figure 13.12

1 2 3 4 5 6 7 8 9

Available-to-PromisePERIOD

ON-HAND = 50 1 2 3 4 5 6

Forecast 100 100 100 100 100 100Customer ordersMaster production schedule 200 200 200Available to promise

PERIOD

ON-HAND = 50 1 2 3 4 5 6

Forecast 100 100 100 100 100 100Customer orders 90 120 130 70 20 10Master production schedule 200 200 200Available to promise 40 0 170

ATP in period 1 = (50 + 200) - (90 + 120) = 40ATP in period 3 = 200 - (130 + 70) = 0ATP in period 5 = 200 - (20 + 10) = 170

Available-to-PromiseProduct Request

Is the product available at

this location?

Is an alternative product available

at an alternate location?

Is an alternative product available at this location?

Is this product available at a

different location?

Available-to-promise

Allocate inventory

Capable-to-promise date

Is the customer willing to wait for

the product?

Available-to-promise

Allocate inventory

Revise master schedule

Trigger production

Lose sale

Yes

No

Yes

No

Yes

No

Yes

No

Yes

No

1. Most services can’t be inventoried

2. Demand for services is difficult to predict

3. Capacity availability is also difficult to predict

4. Service capacity must be provided at the appropriate place and time

5. Labor is usually the most constraining resource for services

6. Labor flexibility can be an advantage in services

Aggregate Planning for Services

Characteristics That Make Yield Management Work

Service or product can be sold in advance of consumption

Demand fluctuatesCapacity is relatively fixedDemand can be segmentedVariable costs are low and fixed costs are

high

Hotel: Single Price Level

$15 variable cost of room

$150 Price charged for room

Price

Sales

$sales = Net price * 50 rooms =150*50=$7500

Demand Curve

Passed up profit contributions

Money left on the table

Potential customers exist who are willing to pay more than the $15 variable cost

Some customers who paid $150 for the room were actually willing to pay more

$ Sales = $ 6,750

Hotel: Two Price Levels

$15 variable cost of room

Demand

Sales

$100Price #1

$200Price #2

Total sales =

1st net price *30 + 2nd net price *30

= $8100

Net prices are:Price #1 => $85Price #2 => $175

$Sales = $ 8,100

Yield Management

P(n < x) Cu

Cu + Co

where

n = number of no-showsx = number of rooms or seats overbooked

Cu = cost of underbooking; i.e., lost saleCo = cost of overbooking; i.e., replacement costP = probability

Yield Management

NO-SHOWS PROBABILITY

0 .151 .25

2 .303 .30

Yield Management

NO-SHOWS PROBABILITY P(N < X)

0 .15 .001 .25 .152 .30 .403 .30 .70

Expected number of no shows

0(.15) + 1(.25) + 2(.30) + 3(.30) = 1.75

Optimal probability of no-shows

P(n < x) = = .517Cu

Cu + Co

7575 + 70

.517

Yield Management

NO-SHOWSNO-SHOWS PROBABILITYPROBABILITY PP((NN < < XX))

00 .15.15 .00.0011 .25.25 .15.1522 .30.30 .40.4033 .30.30 .70.70

Expected number of no shows

0(.15) + 1(.25) + 2(.30) + 3(.30) = 1.75

Optimal probability of no-shows

P(n < x) = = .517Cu

Cu + Co

7575 + 70

.517.517

Cost of overbooking

[2(.15) + 1(.25)]$70 = $38.50 Cost of bumping customers(.30)$75 = $22.50 Lost revenue from no-shows

$61.00 Total cost of overbooking by2 rooms

Expected savings = ($131.225 - $61) = $70.25 a night

Aggregate Planning. Planning Horizon Aggregate planning: Intermediate-range capacity planning,...

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